From 4b8c285b4b0e693443736faffdcbd7c2a48a103e Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Tue, 4 Feb 2025 00:24:26 +0000 Subject: [PATCH] Update results from daily run --- data/output.csv | 2 ++ data/output.json | 2 +- data/updated | 2 +- 3 files changed, 4 insertions(+), 2 deletions(-) diff --git a/data/output.csv b/data/output.csv index 33423b9..dd569f2 100644 --- a/data/output.csv +++ b/data/output.csv @@ -11,6 +11,7 @@ id,name,created,context_length,pricing.prompt,pricing.completion "perplexity/sonar","Perplexity: Sonar",1738013808,127072,"0.000001","0.000001" "liquid/lfm-7b","Liquid: LFM 7B",1737806883,32768,"0.00000001","0.00000001" "liquid/lfm-3b","Liquid: LFM 3B",1737806501,32768,"0.00000002","0.00000002" +"deepseek/deepseek-r1-distill-llama-70b:free","DeepSeek: DeepSeek R1 Distill Llama 70B (free)",1737663169,8192,"0","0" "deepseek/deepseek-r1-distill-llama-70b","DeepSeek: DeepSeek R1 Distill Llama 70B",1737663169,131072,"0.00000023","0.00000069" "google/gemini-2.0-flash-thinking-exp:free","Google: Gemini 2.0 Flash Thinking Experimental 01-21 (free)",1737547899,1048576,"0","0" "deepseek/deepseek-r1:free","DeepSeek: DeepSeek R1 (free)",1737381095,128000,"0","0" @@ -63,6 +64,7 @@ id,name,created,context_length,pricing.prompt,pricing.completion "mistralai/ministral-8b","Mistral: Ministral 8B",1729123200,128000,"0.0000001","0.0000001" "mistralai/ministral-3b","Mistral: Ministral 3B",1729123200,128000,"0.00000004","0.00000004" "qwen/qwen-2.5-7b-instruct","Qwen2.5 7B Instruct",1729036800,32768,"0.000000025","0.00000005" +"nvidia/llama-3.1-nemotron-70b-instruct:free","NVIDIA: Llama 3.1 Nemotron 70B Instruct (free)",1728950400,131072,"0","0" "nvidia/llama-3.1-nemotron-70b-instruct","NVIDIA: Llama 3.1 Nemotron 70B Instruct",1728950400,131000,"0.00000012","0.0000003" "inflection/inflection-3-pi","Inflection: Inflection 3 Pi",1728604800,8000,"0.0000025","0.00001" "inflection/inflection-3-productivity","Inflection: Inflection 3 Productivity",1728604800,8000,"0.0000025","0.00001" diff --git a/data/output.json b/data/output.json index ec1a8e8..dae5a3f 100644 --- a/data/output.json +++ b/data/output.json @@ -1 +1 @@ -{"data":[{"id":"qwen/qwen-turbo","name":"Qwen: Qwen-Turbo","created":1738410974,"description":"Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.","context_length":1000000,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.00000005","completion":"0.0000002","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-plus","name":"Qwen: Qwen-Plus","created":1738409840,"description":"Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.0000004","completion":"0.0000012","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-max","name":"Qwen: Qwen-Max ","created":1738402289,"description":"Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-trained with curated Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) methodologies. The parameter count is unknown.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.0000016","completion":"0.0000064","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"openai/o3-mini","name":"OpenAI: o3 Mini","created":1738351721,"description":"OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities.\n\nThe model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.","context_length":200000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000011","completion":"0.0000044","image":"0","request":"0"},"top_provider":{"context_length":200000,"max_completion_tokens":100000,"is_moderated":true},"per_request_limits":null},{"id":"deepseek/deepseek-r1-distill-qwen-1.5b","name":"Deepseek: Deepseek R1 Distill Qwen 1.5B","created":1738328067,"description":"DeepSeek R1 Distill Qwen 1.5B is a distilled large language model based on [Qwen 2.5 Math 1.5B](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It's a very small and efficient model which outperforms [GPT 4o 0513](/openai/gpt-4o-2024-05-13) on Math Benchmarks.\n\nOther benchmark results include:\n\n- AIME 2024 pass@1: 28.9\n- AIME 2024 cons@64: 52.7\n- MATH-500 pass@1: 83.9\n\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.00000018","completion":"0.00000018","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Mistral: Mistral Small 3","created":1738255409,"description":"Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed for efficient local deployment.\n\nThe model achieves 81% accuracy on the MMLU benchmark and performs competitively with larger models like Llama 3.3 70B and Qwen 32B, while operating at three times the speed on equivalent hardware. [Read the blog post about the model here.](https://mistral.ai/news/mistral-small-3/)","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.00000007","completion":"0.00000014","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-r1-distill-qwen-32b","name":"DeepSeek: DeepSeek R1 Distill Qwen 32B","created":1738194830,"description":"DeepSeek R1 Distill Qwen 32B is a distilled large language model based on [Qwen 2.5 32B](https://huggingface.co/Qwen/Qwen2.5-32B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models.\n\nOther benchmark results include:\n\n- AIME 2024 pass@1: 72.6\n- MATH-500 pass@1: 94.3\n- CodeForces Rating: 1691\n\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.00000012","completion":"0.00000018","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-r1-distill-qwen-14b","name":"DeepSeek: DeepSeek R1 Distill Qwen 14B","created":1738193940,"description":"DeepSeek R1 Distill Qwen 14B is a distilled large language model based on [Qwen 2.5 14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models.\n\nOther benchmark results include:\n\n- AIME 2024 pass@1: 69.7\n- MATH-500 pass@1: 93.9\n- CodeForces Rating: 1481\n\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.0000016","completion":"0.0000016","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/sonar-reasoning","name":"Perplexity: Sonar Reasoning","created":1738131107,"description":"Sonar Reasoning is a reasoning model provided by Perplexity based on [DeepSeek R1](/deepseek/deepseek-r1).\n\nIt allows developers to utilize long chain of thought with built-in web search. Sonar Reasoning is uncensored and hosted in US datacenters. ","context_length":127000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.000001","completion":"0.000005","image":"0","request":"0.005"},"top_provider":{"context_length":127000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/sonar","name":"Perplexity: Sonar","created":1738013808,"description":"Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources. It is designed for companies seeking to integrate lightweight question-and-answer features optimized for speed.","context_length":127072,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.000001","completion":"0.000001","image":"0","request":"0.005"},"top_provider":{"context_length":127072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"liquid/lfm-7b","name":"Liquid: LFM 7B","created":1737806883,"description":"LFM-7B, a new best-in-class language model. LFM-7B is designed for exceptional chat capabilities, including languages like Arabic and Japanese. Powered by the Liquid Foundation Model (LFM) architecture, it exhibits unique features like low memory footprint and fast inference speed. \n\nLFM-7B is the world’s best-in-class multilingual language model in English, Arabic, and Japanese.\n\nSee the [launch announcement](https://www.liquid.ai/lfm-7b) for benchmarks and more info.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":"chatml"},"pricing":{"prompt":"0.00000001","completion":"0.00000001","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"liquid/lfm-3b","name":"Liquid: LFM 3B","created":1737806501,"description":"Liquid's LFM 3B delivers incredible performance for its size. It positions itself as first place among 3B parameter transformers, hybrids, and RNN models It is also on par with Phi-3.5-mini on multiple benchmarks, while being 18.4% smaller.\n\nLFM-3B is the ideal choice for mobile and other edge text-based applications.\n\nSee the [launch announcement](https://www.liquid.ai/liquid-foundation-models) for benchmarks and more info.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":"chatml"},"pricing":{"prompt":"0.00000002","completion":"0.00000002","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-r1-distill-llama-70b","name":"DeepSeek: DeepSeek R1 Distill Llama 70B","created":1737663169,"description":"DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across multiple benchmarks, including:\n\n- AIME 2024 pass@1: 70.0\n- MATH-500 pass@1: 94.5\n- CodeForces Rating: 1633\n\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.00000023","completion":"0.00000069","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-2.0-flash-thinking-exp:free","name":"Google: Gemini 2.0 Flash Thinking Experimental 01-21 (free)","created":1737547899,"description":"Gemini 2.0 Flash Thinking Experimental (01-21) is a snapshot of Gemini 2.0 Flash Thinking Experimental.\n\nGemini 2.0 Flash Thinking Mode is an experimental model that's trained to generate the \"thinking process\" the model goes through as part of its response. As a result, Thinking Mode is capable of stronger reasoning capabilities in its responses than the [base Gemini 2.0 Flash model](/google/gemini-2.0-flash-exp).","context_length":1048576,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":1048576,"max_completion_tokens":65536,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-r1:free","name":"DeepSeek: DeepSeek R1 (free)","created":1737381095,"description":"DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.\n\nFully open-source model & [technical report](https://api-docs.deepseek.com/news/news250120).\n\nMIT licensed: Distill & commercialize freely!","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"DeepSeek","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-r1","name":"DeepSeek: DeepSeek R1","created":1737381095,"description":"DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.\n\nFully open-source model & [technical report](https://api-docs.deepseek.com/news/news250120).\n\nMIT licensed: Distill & commercialize freely!","context_length":16000,"architecture":{"modality":"text->text","tokenizer":"DeepSeek","instruct_type":null},"pricing":{"prompt":"0.00000075","completion":"0.0000024","image":"0","request":"0"},"top_provider":{"context_length":16000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-r1:nitro","name":"DeepSeek: DeepSeek R1 (nitro)","created":1737381095,"description":"DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.\n\nFully open-source model & [technical report](https://api-docs.deepseek.com/news/news250120).\n\nMIT licensed: Distill & commercialize freely!","context_length":163840,"architecture":{"modality":"text->text","tokenizer":"DeepSeek","instruct_type":null},"pricing":{"prompt":"0.000007","completion":"0.000007","image":"0","request":"0"},"top_provider":{"context_length":163840,"max_completion_tokens":32768,"is_moderated":false},"per_request_limits":null},{"id":"sophosympatheia/rogue-rose-103b-v0.2:free","name":"Rogue Rose 103B v0.2 (free)","created":1737195189,"description":"Rogue Rose demonstrates strong capabilities in roleplaying and storytelling applications, potentially surpassing other models in the 103-120B parameter range. While it occasionally exhibits inconsistencies with scene logic, the overall interaction quality represents an advancement in natural language processing for creative applications.\n\nIt is a 120-layer frankenmerge model combining two custom 70B architectures from November 2023, derived from the [xwin-stellarbright-erp-70b-v2](https://huggingface.co/sophosympatheia/xwin-stellarbright-erp-70b-v2) base.\n","context_length":4096,"architecture":{"modality":"text->text","tokenizer":"Llama2","instruct_type":"vicuna"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"minimax/minimax-01","name":"MiniMax: MiniMax-01","created":1736915462,"description":"MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per inference, and can handle a context of up to 4 million tokens.\n\nThe text model adopts a hybrid architecture that combines Lightning Attention, Softmax Attention, and Mixture-of-Experts (MoE). The image model adopts the “ViT-MLP-LLM” framework and is trained on top of the text model.\n\nTo read more about the release, see: https://www.minimaxi.com/en/news/minimax-01-series-2","context_length":1000192,"architecture":{"modality":"text+image->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000002","completion":"0.0000011","image":"0","request":"0"},"top_provider":{"context_length":1000192,"max_completion_tokens":1000192,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/codestral-2501","name":"Mistral: Codestral 2501","created":1736895522,"description":"[Mistral](/mistralai)'s cutting-edge language model for coding. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. \n\nLearn more on their blog post: https://mistral.ai/news/codestral-2501/","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.0000003","completion":"0.0000009","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"microsoft/phi-4","name":"Microsoft: Phi 4","created":1736489872,"description":"[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. \n\nAt 14 billion parameters, it was trained on a mix of high-quality synthetic datasets, data from curated websites, and academic materials. It has undergone careful improvement to follow instructions accurately and maintain strong safety standards. It works best with English language inputs.\n\nFor more information, please see [Phi-4 Technical Report](https://arxiv.org/pdf/2412.08905)\n","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.00000007","completion":"0.00000014","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"sao10k/l3.1-70b-hanami-x1","name":"Sao10K: Llama 3.1 70B Hanami x1","created":1736302854,"description":"This is [Sao10K](/sao10k)'s experiment over [Euryale v2.2](/sao10k/l3.1-euryale-70b).","context_length":16000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000003","image":"0","request":"0"},"top_provider":{"context_length":16000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-chat","name":"DeepSeek: DeepSeek V3","created":1735241320,"description":"DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. Pre-trained on nearly 15 trillion tokens, the reported evaluations reveal that the model outperforms other open-source models and rivals leading closed-source models.\n\nFor model details, please visit [the DeepSeek-V3 repo](https://github.com/deepseek-ai/DeepSeek-V3) for more information, or see the [launch announcement](https://api-docs.deepseek.com/news/news1226).","context_length":16000,"architecture":{"modality":"text->text","tokenizer":"DeepSeek","instruct_type":null},"pricing":{"prompt":"0.00000049","completion":"0.00000089","image":"0","request":"0"},"top_provider":{"context_length":16000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qvq-72b-preview","name":"Qwen: QvQ 72B Preview","created":1735088567,"description":"QVQ-72B-Preview is an experimental research model developed by the [Qwen](/qwen) team, focusing on enhancing visual reasoning capabilities.\n\n## Performance\n\n| | **QVQ-72B-Preview** | o1-2024-12-17 | gpt-4o-2024-05-13 | Claude3.5 Sonnet-20241022 | Qwen2VL-72B |\n|----------------|-----------------|---------------|-------------------|----------------------------|-------------|\n| MMMU(val) | 70.3 | 77.3 | 69.1 | 70.4 | 64.5 |\n| MathVista(mini) | 71.4 | 71.0 | 63.8 | 65.3 | 70.5 |\n| MathVision(full) | 35.9 | – | 30.4 | 35.6 | 25.9 |\n| OlympiadBench | 20.4 | – | 25.9 | – | 11.2 |\n\n\n## Limitations\n\n1. **Language Mixing and Code-Switching:** The model might occasionally mix different languages or unexpectedly switch between them, potentially affecting the clarity of its responses.\n2. **Recursive Reasoning Loops:** There's a risk of the model getting caught in recursive reasoning loops, leading to lengthy responses that may not even arrive at a final answer.\n3. **Safety and Ethical Considerations:** Robust safety measures are needed to ensure reliable and safe performance. Users should exercise caution when deploying this model.\n4. **Performance and Benchmark Limitations:** Despite the improvements in visual reasoning, QVQ doesn’t entirely replace the capabilities of [Qwen2-VL-72B](/qwen/qwen-2-vl-72b-instruct). During multi-step visual reasoning, the model might gradually lose focus on the image content, leading to hallucinations. Moreover, QVQ doesn’t show significant improvement over [Qwen2-VL-72B](/qwen/qwen-2-vl-72b-instruct) in basic recognition tasks like identifying people, animals, or plants.\n\nNote: Currently, the model only supports single-round dialogues and image outputs. It does not support video inputs.","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.00000025","completion":"0.0000005","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-2.0-flash-thinking-exp-1219:free","name":"Google: Gemini 2.0 Flash Thinking Experimental (free)","created":1734650026,"description":"Gemini 2.0 Flash Thinking Mode is an experimental model that's trained to generate the \"thinking process\" the model goes through as part of its response. As a result, Thinking Mode is capable of stronger reasoning capabilities in its responses than the [base Gemini 2.0 Flash model](/google/gemini-2.0-flash-exp).","context_length":40000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":40000,"max_completion_tokens":8000,"is_moderated":false},"per_request_limits":null},{"id":"sao10k/l3.3-euryale-70b","name":"Sao10K: Llama 3.3 Euryale 70B","created":1734535928,"description":"Euryale L3.3 70B is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.2](/models/sao10k/l3-euryale-70b).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000007","completion":"0.0000008","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"openai/o1","name":"OpenAI: o1","created":1734459999,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. \n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n","context_length":200000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.000015","completion":"0.00006","image":"0.021675","request":"0"},"top_provider":{"context_length":200000,"max_completion_tokens":100000,"is_moderated":true},"per_request_limits":null},{"id":"eva-unit-01/eva-llama-3.33-70b","name":"EVA Llama 3.33 70b","created":1734377303,"description":"EVA Llama 3.33 70b is a roleplay and storywriting specialist model. 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From object recognition to style analysis, it empowers developers to build more intuitive, visually aware applications. 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Sonnet is particularly good at:\n\n- Coding: Scores ~49% on SWE-Bench Verified, higher than the last best score, and without any fancy prompt scaffolding\n- Data science: Augments human data science expertise; navigates unstructured data while using multiple tools for insights\n- Visual processing: excelling at interpreting charts, graphs, and images, accurately transcribing text to derive insights beyond just the text alone\n- Agentic tasks: exceptional tool use, making it great at agentic tasks (i.e. complex, multi-step problem solving tasks that require engaging with other systems)\n\n#multimodal","context_length":200000,"architecture":{"modality":"text+image->text","tokenizer":"Claude","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000015","image":"0.0048","request":"0"},"top_provider":{"context_length":200000,"max_completion_tokens":8192,"is_moderated":true},"per_request_limits":null},{"id":"x-ai/grok-beta","name":"xAI: Grok Beta","created":1729382400,"description":"Grok Beta is xAI's experimental language model with state-of-the-art reasoning capabilities, best for complex and multi-step use cases.\n\nIt is the successor of [Grok 2](https://x.ai/blog/grok-2) with enhanced context length.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Grok","instruct_type":null},"pricing":{"prompt":"0.000005","completion":"0.000015","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/ministral-8b","name":"Mistral: Ministral 8B","created":1729123200,"description":"Ministral 8B is an 8B parameter model featuring a unique interleaved sliding-window attention pattern for faster, memory-efficient inference. 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Supporting up to 128k context length, it’s ideal for orchestrating agentic workflows and specialist tasks with efficient inference.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.00000004","completion":"0.00000004","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2.5-7b-instruct","name":"Qwen2.5 7B Instruct","created":1729036800,"description":"Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2:\n\n- Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains.\n\n- Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots.\n\n- Long-context Support up to 128K tokens and can generate up to 8K tokens.\n\n- Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000000025","completion":"0.00000005","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"nvidia/llama-3.1-nemotron-70b-instruct","name":"NVIDIA: Llama 3.1 Nemotron 70B Instruct","created":1728950400,"description":"NVIDIA's Llama 3.1 Nemotron 70B is a language model designed for generating precise and useful responses. Leveraging [Llama 3.1 70B](/models/meta-llama/llama-3.1-70b-instruct) architecture and Reinforcement Learning from Human Feedback (RLHF), it excels in automatic alignment benchmarks. This model is tailored for applications requiring high accuracy in helpfulness and response generation, suitable for diverse user queries across multiple domains.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000012","completion":"0.0000003","image":"0","request":"0"},"top_provider":{"context_length":131000,"max_completion_tokens":131000,"is_moderated":false},"per_request_limits":null},{"id":"inflection/inflection-3-pi","name":"Inflection: Inflection 3 Pi","created":1728604800,"description":"Inflection 3 Pi powers Inflection's [Pi](https://pi.ai) chatbot, including backstory, emotional intelligence, productivity, and safety. It has access to recent news, and excels in scenarios like customer support and roleplay.\n\nPi has been trained to mirror your tone and style, if you use more emojis, so will Pi! Try experimenting with various prompts and conversation styles.","context_length":8000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000025","completion":"0.00001","image":"0","request":"0"},"top_provider":{"context_length":8000,"max_completion_tokens":1024,"is_moderated":false},"per_request_limits":null},{"id":"inflection/inflection-3-productivity","name":"Inflection: Inflection 3 Productivity","created":1728604800,"description":"Inflection 3 Productivity is optimized for following instructions. It is better for tasks requiring JSON output or precise adherence to provided guidelines. It has access to recent news.\n\nFor emotional intelligence similar to Pi, see [Inflect 3 Pi](/inflection/inflection-3-pi)\n\nSee [Inflection's announcement](https://inflection.ai/blog/enterprise) for more details.","context_length":8000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000025","completion":"0.00001","image":"0","request":"0"},"top_provider":{"context_length":8000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-flash-1.5-8b","name":"Google: Gemini Flash 1.5 8B","created":1727913600,"description":"Gemini Flash 1.5 8B is optimized for speed and efficiency, offering enhanced performance in small prompt tasks like chat, transcription, and translation. With reduced latency, it is highly effective for real-time and large-scale operations. This model focuses on cost-effective solutions while maintaining high-quality results.\n\n[Click here to learn more about this model](https://developers.googleblog.com/en/gemini-15-flash-8b-is-now-generally-available-for-use/).\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).","context_length":1000000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0.0000000375","completion":"0.00000015","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"anthracite-org/magnum-v2-72b","name":"Magnum v2 72B","created":1727654400,"description":"From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the seventh in a family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.\n\nThe model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000003","completion":"0.000003","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"liquid/lfm-40b","name":"Liquid: LFM 40B MoE","created":1727654400,"description":"Liquid's 40.3B Mixture of Experts (MoE) model. Liquid Foundation Models (LFMs) are large neural networks built with computational units rooted in dynamic systems.\n\nLFMs are general-purpose AI models that can be used to model any kind of sequential data, including video, audio, text, time series, and signals.\n\nSee the [launch announcement](https://www.liquid.ai/liquid-foundation-models) for benchmarks and more info.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":"chatml"},"pricing":{"prompt":"0.00000015","completion":"0.00000015","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"thedrummer/rocinante-12b","name":"Rocinante 12B","created":1727654400,"description":"Rocinante 12B is designed for engaging storytelling and rich prose.\n\nEarly testers have reported:\n- Expanded vocabulary with unique and expressive word choices\n- Enhanced creativity for vivid narratives\n- Adventure-filled and captivating stories","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.00000025","completion":"0.0000005","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-3b-instruct:free","name":"Meta: Llama 3.2 3B Instruct (free)","created":1727222400,"description":"Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages.\n\nTrained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":4096,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-3b-instruct","name":"Meta: Llama 3.2 3B Instruct","created":1727222400,"description":"Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages.\n\nTrained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.000000015","completion":"0.000000025","image":"0","request":"0"},"top_provider":{"context_length":131000,"max_completion_tokens":131000,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-1b-instruct:free","name":"Meta: Llama 3.2 1B Instruct (free)","created":1727222400,"description":"Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance.\n\nSupporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":4096,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-1b-instruct","name":"Meta: Llama 3.2 1B Instruct","created":1727222400,"description":"Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance.\n\nSupporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000001","completion":"0.00000001","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-90b-vision-instruct:free","name":"Meta: Llama 3.2 90B Vision Instruct (free)","created":1727222400,"description":"The Llama 90B Vision model is a top-tier, 90-billion-parameter multimodal model designed for the most challenging visual reasoning and language tasks. It offers unparalleled accuracy in image captioning, visual question answering, and advanced image-text comprehension. Pre-trained on vast multimodal datasets and fine-tuned with human feedback, the Llama 90B Vision is engineered to handle the most demanding image-based AI tasks.\n\nThis model is perfect for industries requiring cutting-edge multimodal AI capabilities, particularly those dealing with complex, real-time visual and textual analysis.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":4096,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-90b-vision-instruct","name":"Meta: Llama 3.2 90B Vision Instruct","created":1727222400,"description":"The Llama 90B Vision model is a top-tier, 90-billion-parameter multimodal model designed for the most challenging visual reasoning and language tasks. It offers unparalleled accuracy in image captioning, visual question answering, and advanced image-text comprehension. Pre-trained on vast multimodal datasets and fine-tuned with human feedback, the Llama 90B Vision is engineered to handle the most demanding image-based AI tasks.\n\nThis model is perfect for industries requiring cutting-edge multimodal AI capabilities, particularly those dealing with complex, real-time visual and textual analysis.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000009","completion":"0.0000009","image":"0.001301","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-11b-vision-instruct:free","name":"Meta: Llama 3.2 11B Vision Instruct (free)","created":1727222400,"description":"Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis.\n\nIts ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-11b-vision-instruct","name":"Meta: Llama 3.2 11B Vision Instruct","created":1727222400,"description":"Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis.\n\nIts ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.000000055","completion":"0.000000055","image":"0.00007948","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B Instruct","created":1726704000,"description":"Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2:\n\n- Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains.\n\n- Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots.\n\n- Long-context Support up to 128K tokens and can generate up to 8K tokens.\n\n- Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.00000023","completion":"0.0000004","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2-vl-72b-instruct","name":"Qwen2-VL 72B Instruct","created":1726617600,"description":"Qwen2 VL 72B is a multimodal LLM from the Qwen Team with the following key enhancements:\n\n- SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc.\n\n- Understanding videos of 20min+: Qwen2-VL can understand videos over 20 minutes for high-quality video-based question answering, dialog, content creation, etc.\n\n- Agent that can operate your mobiles, robots, etc.: with the abilities of complex reasoning and decision making, Qwen2-VL can be integrated with devices like mobile phones, robots, etc., for automatic operation based on visual environment and text instructions.\n\n- Multilingual Support: to serve global users, besides English and Chinese, Qwen2-VL now supports the understanding of texts in different languages inside images, including most European languages, Japanese, Korean, Arabic, Vietnamese, etc.\n\nFor more details, see this [blog post](https://qwenlm.github.io/blog/qwen2-vl/) and [GitHub repo](https://github.com/QwenLM/Qwen2-VL).\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":4096,"architecture":{"modality":"text+image->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.0000004","completion":"0.0000004","image":"0.000578","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"neversleep/llama-3.1-lumimaid-8b","name":"NeverSleep: Lumimaid v0.2 8B","created":1726358400,"description":"Lumimaid v0.2 8B is a finetune of [Llama 3.1 8B](/models/meta-llama/llama-3.1-8b-instruct) with a \"HUGE step up dataset wise\" compared to Lumimaid v0.1. Sloppy chats output were purged.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000001875","completion":"0.000001125","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"openai/o1-mini-2024-09-12","name":"OpenAI: o1-mini (2024-09-12)","created":1726099200,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.0000011","completion":"0.0000044","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":65536,"is_moderated":true},"per_request_limits":null},{"id":"openai/o1-preview","name":"OpenAI: o1-preview","created":1726099200,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.000015","completion":"0.00006","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":32768,"is_moderated":true},"per_request_limits":null},{"id":"openai/o1-preview-2024-09-12","name":"OpenAI: o1-preview (2024-09-12)","created":1726099200,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.000015","completion":"0.00006","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":32768,"is_moderated":true},"per_request_limits":null},{"id":"openai/o1-mini","name":"OpenAI: o1-mini","created":1726099200,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.0000011","completion":"0.0000044","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":65536,"is_moderated":true},"per_request_limits":null},{"id":"mistralai/pixtral-12b","name":"Mistral: Pixtral 12B","created":1725926400,"description":"The first multi-modal, text+image-to-text model from Mistral AI. Its weights were launched via torrent: https://x.com/mistralai/status/1833758285167722836.","context_length":4096,"architecture":{"modality":"text+image->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.0000001","completion":"0.0000001","image":"0.0001445","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"cohere/command-r-08-2024","name":"Cohere: Command R (08-2024)","created":1724976000,"description":"command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and is competitive with the previous version of the larger Command R+ model.\n\nRead the launch post [here](https://docs.cohere.com/changelog/command-gets-refreshed).\n\nUse of this model is subject to Cohere's [Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy).","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"Cohere","instruct_type":null},"pricing":{"prompt":"0.0000001425","completion":"0.00000057","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":4000,"is_moderated":false},"per_request_limits":null},{"id":"cohere/command-r-plus-08-2024","name":"Cohere: Command R+ (08-2024)","created":1724976000,"description":"command-r-plus-08-2024 is an update of the [Command R+](/models/cohere/command-r-plus) with roughly 50% higher throughput and 25% lower latencies as compared to the previous Command R+ version, while keeping the hardware footprint the same.\n\nRead the launch post [here](https://docs.cohere.com/changelog/command-gets-refreshed).\n\nUse of this model is subject to Cohere's [Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy).","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"Cohere","instruct_type":null},"pricing":{"prompt":"0.000002375","completion":"0.0000095","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":4000,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2-vl-7b-instruct","name":"Qwen2-VL 7B Instruct","created":1724803200,"description":"Qwen2 VL 7B is a multimodal LLM from the Qwen Team with the following key enhancements:\n\n- SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc.\n\n- Understanding videos of 20min+: Qwen2-VL can understand videos over 20 minutes for high-quality video-based question answering, dialog, content creation, etc.\n\n- Agent that can operate your mobiles, robots, etc.: with the abilities of complex reasoning and decision making, Qwen2-VL can be integrated with devices like mobile phones, robots, etc., for automatic operation based on visual environment and text instructions.\n\n- Multilingual Support: to serve global users, besides English and Chinese, Qwen2-VL now supports the understanding of texts in different languages inside images, including most European languages, Japanese, Korean, Arabic, Vietnamese, etc.\n\nFor more details, see this [blog post](https://qwenlm.github.io/blog/qwen2-vl/) and [GitHub repo](https://github.com/QwenLM/Qwen2-VL).\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":4096,"architecture":{"modality":"text+image->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.0000001","completion":"0.0000001","image":"0.0001445","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-flash-1.5-exp:free","name":"Google: Gemini Flash 1.5 Experimental (free)","created":1724803200,"description":"Gemini 1.5 Flash Experimental is an experimental version of the [Gemini 1.5 Flash](/models/google/gemini-flash-1.5) model.\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).\n\n#multimodal\n\nNote: This model is experimental and not suited for production use-cases. 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It may be removed or redirected to another model in the future.","context_length":1000000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"sao10k/l3.1-euryale-70b","name":"Sao10K: Llama 3.1 Euryale 70B v2.2","created":1724803200,"description":"Euryale L3.1 70B v2.2 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.1](/models/sao10k/l3-euryale-70b).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000007","completion":"0.0000008","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-flash-1.5-8b-exp","name":"Google: Gemini Flash 1.5 8B Experimental","created":1724803200,"description":"Gemini Flash 1.5 8B Experimental is an experimental, 8B parameter version of the [Gemini Flash 1.5](/models/google/gemini-flash-1.5) model.\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).\n\n#multimodal\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":1000000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"ai21/jamba-1-5-large","name":"AI21: Jamba 1.5 Large","created":1724371200,"description":"Jamba 1.5 Large is part of AI21's new family of open models, offering superior speed, efficiency, and quality.\n\nIt features a 256K effective context window, the longest among open models, enabling improved performance on tasks like document summarization and analysis.\n\nBuilt on a novel SSM-Transformer architecture, it outperforms larger models like Llama 3.1 70B on benchmarks while maintaining resource efficiency.\n\nRead their [announcement](https://www.ai21.com/blog/announcing-jamba-model-family) to learn more.","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.000002","completion":"0.000008","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"ai21/jamba-1-5-mini","name":"AI21: Jamba 1.5 Mini","created":1724371200,"description":"Jamba 1.5 Mini is the world's first production-grade Mamba-based model, combining SSM and Transformer architectures for a 256K context window and high efficiency.\n\nIt works with 9 languages and can handle various writing and analysis tasks as well as or better than similar small models.\n\nThis model uses less computer memory and works faster with longer texts than previous designs.\n\nRead their [announcement](https://www.ai21.com/blog/announcing-jamba-model-family) to learn more.","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000002","completion":"0.0000004","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"microsoft/phi-3.5-mini-128k-instruct","name":"Microsoft: Phi-3.5 Mini 128K Instruct","created":1724198400,"description":"Phi-3.5 models are lightweight, state-of-the-art open models. 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When assessed against benchmarks that test common sense, language understanding, math, code, long context and logical reasoning, Phi-3.5 models showcased robust and state-of-the-art performance among models with less than 13 billion parameters.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":"phi3"},"pricing":{"prompt":"0.0000001","completion":"0.0000001","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"nousresearch/hermes-3-llama-3.1-70b","name":"Nous: Hermes 3 70B Instruct","created":1723939200,"description":"Hermes 3 is a generalist language model with many improvements over [Hermes 2](/models/nousresearch/nous-hermes-2-mistral-7b-dpo), including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the board.\n\nHermes 3 70B is a competitive, if not superior finetune of the [Llama-3.1 70B foundation model](/models/meta-llama/llama-3.1-70b-instruct), focused on aligning LLMs to the user, with powerful steering capabilities and control given to the end user.\n\nThe Hermes 3 series builds and expands on the Hermes 2 set of capabilities, including more powerful and reliable function calling and structured output capabilities, generalist assistant capabilities, and improved code generation skills.","context_length":131000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"chatml"},"pricing":{"prompt":"0.00000012","completion":"0.0000003","image":"0","request":"0"},"top_provider":{"context_length":131000,"max_completion_tokens":131000,"is_moderated":false},"per_request_limits":null},{"id":"nousresearch/hermes-3-llama-3.1-405b","name":"Nous: Hermes 3 405B Instruct","created":1723766400,"description":"Hermes 3 is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the board.\n\nHermes 3 405B is a frontier-level, full-parameter finetune of the Llama-3.1 405B foundation model, focused on aligning LLMs to the user, with powerful steering capabilities and control given to the end user.\n\nThe Hermes 3 series builds and expands on the Hermes 2 set of capabilities, including more powerful and reliable function calling and structured output capabilities, generalist assistant capabilities, and improved code generation skills.\n\nHermes 3 is competitive, if not superior, to Llama-3.1 Instruct models at general capabilities, with varying strengths and weaknesses attributable between the two.","context_length":131000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"chatml"},"pricing":{"prompt":"0.0000008","completion":"0.0000008","image":"0","request":"0"},"top_provider":{"context_length":131000,"max_completion_tokens":131000,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-huge-128k-online","name":"Perplexity: Llama 3.1 Sonar 405B Online","created":1723593600,"description":"Llama 3.1 Sonar is Perplexity's latest model family. 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It is intended for research and evaluation.\n\nOpenAI notes that this model is not suited for production use-cases as it may be removed or redirected to another model in the future.","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.000005","completion":"0.000015","image":"0.007225","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":16384,"is_moderated":true},"per_request_limits":null},{"id":"sao10k/l3-lunaris-8b","name":"Sao10K: Llama 3 8B Lunaris","created":1723507200,"description":"Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It's a strategic merge of multiple models, designed to balance creativity with improved logic and general knowledge.\n\nCreated by [Sao10k](https://huggingface.co/Sao10k), this model aims to offer an improved experience over Stheno v3.2, with enhanced creativity and logical reasoning.\n\nFor best results, use with Llama 3 Instruct context template, temperature 1.4, and min_p 0.1.","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000003","completion":"0.00000006","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"aetherwiing/mn-starcannon-12b","name":"Aetherwiing: Starcannon 12B","created":1723507200,"description":"Starcannon 12B v2 is a creative roleplay and story writing model, based on Mistral Nemo, using [nothingiisreal/mn-celeste-12b](/nothingiisreal/mn-celeste-12b) as a base, with [intervitens/mini-magnum-12b-v1.1](https://huggingface.co/intervitens/mini-magnum-12b-v1.1) merged in using the [TIES](https://arxiv.org/abs/2306.01708) method.\n\nAlthough more similar to Magnum overall, the model remains very creative, with a pleasant writing style. It is recommended for people wanting more variety than Magnum, and yet more verbose prose than Celeste.","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"chatml"},"pricing":{"prompt":"0.0000008","completion":"0.0000012","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"openai/gpt-4o-2024-08-06","name":"OpenAI: GPT-4o (2024-08-06)","created":1722902400,"description":"The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format. Read more [here](https://openai.com/index/introducing-structured-outputs-in-the-api/).\n\nGPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.\n\nFor benchmarking against other models, it was briefly called [\"im-also-a-good-gpt2-chatbot\"](https://twitter.com/LiamFedus/status/1790064963966370209)","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.0000025","completion":"0.00001","image":"0.003613","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":16384,"is_moderated":true},"per_request_limits":null},{"id":"meta-llama/llama-3.1-405b","name":"Meta: Llama 3.1 405B (base)","created":1722556800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This is the base 405B pre-trained version.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"none"},"pricing":{"prompt":"0.000002","completion":"0.000002","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"nothingiisreal/mn-celeste-12b","name":"Mistral Nemo 12B Celeste","created":1722556800,"description":"A specialized story writing and roleplaying model based on Mistral's NeMo 12B Instruct. 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It demonstrates remarkable versatility in both SFW and NSFW scenarios, with strong Out of Character (OOC) steering capabilities, allowing fine-tuned control over narrative direction and character behavior.\n\nCheck out the model's [HuggingFace page](https://huggingface.co/nothingiisreal/MN-12B-Celeste-V1.9) for details on what parameters and prompts work best!","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"chatml"},"pricing":{"prompt":"0.0000008","completion":"0.0000012","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-small-128k-chat","name":"Perplexity: Llama 3.1 Sonar 8B","created":1722470400,"description":"Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is a normal offline LLM, but the [online version](/models/perplexity/llama-3.1-sonar-small-128k-online) of this model has Internet access.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.0000002","completion":"0.0000002","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-pro-1.5-exp","name":"Google: Gemini Pro 1.5 Experimental","created":1722470400,"description":"Gemini 1.5 Pro Experimental is a bleeding-edge version of the [Gemini 1.5 Pro](/models/google/gemini-pro-1.5) model. Because it's currently experimental, it will be **heavily rate-limited** by Google.\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).\n\n#multimodal","context_length":1000000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-large-128k-chat","name":"Perplexity: Llama 3.1 Sonar 70B","created":1722470400,"description":"Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is a normal offline LLM, but the [online version](/models/perplexity/llama-3.1-sonar-large-128k-online) of this model has Internet access.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.000001","completion":"0.000001","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-large-128k-online","name":"Perplexity: Llama 3.1 Sonar 70B Online","created":1722470400,"description":"Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is the online version of the [offline chat model](/models/perplexity/llama-3.1-sonar-large-128k-chat). It is focused on delivering helpful, up-to-date, and factual responses. #online","context_length":127072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.000001","completion":"0.000001","image":"0","request":"0.005"},"top_provider":{"context_length":127072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-small-128k-online","name":"Perplexity: Llama 3.1 Sonar 8B Online","created":1722470400,"description":"Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is the online version of the [offline chat model](/models/perplexity/llama-3.1-sonar-small-128k-chat). It is focused on delivering helpful, up-to-date, and factual responses. #online","context_length":127072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.0000002","completion":"0.0000002","image":"0","request":"0.005"},"top_provider":{"context_length":127072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-405b-instruct:free","name":"Meta: Llama 3.1 405B Instruct (free)","created":1721692800,"description":"The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":8000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":8000,"max_completion_tokens":4000,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-405b-instruct","name":"Meta: Llama 3.1 405B Instruct","created":1721692800,"description":"The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000008","completion":"0.0000008","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-405b-instruct:nitro","name":"Meta: Llama 3.1 405B Instruct (nitro)","created":1721692800,"description":"The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":8000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00001462","completion":"0.00001462","image":"0","request":"0"},"top_provider":{"context_length":8000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-8b-instruct:free","name":"Meta: Llama 3.1 8B Instruct (free)","created":1721692800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. 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Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":64000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000325","completion":"0.00000325","image":"0","request":"0"},"top_provider":{"context_length":64000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/mistral-nemo","name":"Mistral: Mistral Nemo","created":1721347200,"description":"A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA.\n\nThe model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.\n\nIt supports function calling and is released under the Apache 2.0 license.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"mistral"},"pricing":{"prompt":"0.000000035","completion":"0.00000008","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/codestral-mamba","name":"Mistral: Codestral Mamba","created":1721347200,"description":"A 7.3B parameter Mamba-based model designed for code and reasoning tasks.\n\n- Linear time inference, allowing for theoretically infinite sequence lengths\n- 256k token context window\n- Optimized for quick responses, especially beneficial for code productivity\n- Performs comparably to state-of-the-art transformer models in code and reasoning tasks\n- Available under the Apache 2.0 license for free use, modification, and distribution","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.00000025","completion":"0.00000025","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"openai/gpt-4o-mini","name":"OpenAI: GPT-4o-mini","created":1721260800,"description":"GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.\n\nAs their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than [GPT-3.5 Turbo](/models/openai/gpt-3.5-turbo). It maintains SOTA intelligence, while being significantly more cost-effective.\n\nGPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences [common leaderboards](https://arena.lmsys.org/).\n\nCheck out the [launch announcement](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/) to learn more.\n\n#multimodal","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.00000015","completion":"0.0000006","image":"0.007225","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":16384,"is_moderated":true},"per_request_limits":null},{"id":"openai/gpt-4o-mini-2024-07-18","name":"OpenAI: GPT-4o-mini (2024-07-18)","created":1721260800,"description":"GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.\n\nAs their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than [GPT-3.5 Turbo](/models/openai/gpt-3.5-turbo). It maintains SOTA intelligence, while being significantly more cost-effective.\n\nGPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences [common leaderboards](https://arena.lmsys.org/).\n\nCheck out the [launch announcement](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/) to learn more.\n\n#multimodal","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.00000015","completion":"0.0000006","image":"0.007225","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":16384,"is_moderated":true},"per_request_limits":null},{"id":"qwen/qwen-2-7b-instruct:free","name":"Qwen 2 7B Instruct (free)","created":1721088000,"description":"Qwen2 7B is a transformer-based model that excels in language understanding, multilingual capabilities, coding, mathematics, and reasoning.\n\nIt features SwiGLU activation, attention QKV bias, and group query attention. 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It is pretrained on extensive data with supervised finetuning and direct preference optimization.\n\nFor more details, see this [blog post](https://qwenlm.github.io/blog/qwen2/) and [GitHub repo](https://github.com/QwenLM/Qwen2).\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000000054","completion":"0.000000054","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemma-2-27b-it","name":"Google: Gemma 2 27B","created":1720828800,"description":"Gemma 2 27B by Google is an open model built from the same research and technology used to create the [Gemini models](/models?q=gemini).\n\nGemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning.\n\nSee the [launch announcement](https://blog.google/technology/developers/google-gemma-2/) for more details. Usage of Gemma is subject to Google's [Gemma Terms of Use](https://ai.google.dev/gemma/terms).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Gemini","instruct_type":"gemma"},"pricing":{"prompt":"0.00000027","completion":"0.00000027","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"alpindale/magnum-72b","name":"Magnum 72B","created":1720656000,"description":"From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the first in a new family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.\n\nThe model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000001875","completion":"0.00000225","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":1024,"is_moderated":false},"per_request_limits":null},{"id":"google/gemma-2-9b-it:free","name":"Google: Gemma 2 9B (free)","created":1719532800,"description":"Gemma 2 9B by Google is an advanced, open-source language model that sets a new standard for efficiency and performance in its size class.\n\nDesigned for a wide variety of tasks, it empowers developers and researchers to build innovative applications, while maintaining accessibility, safety, and cost-effectiveness.\n\nSee the [launch announcement](https://blog.google/technology/developers/google-gemma-2/) for more details. Usage of Gemma is subject to Google's [Gemma Terms of Use](https://ai.google.dev/gemma/terms).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Gemini","instruct_type":"gemma"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"google/gemma-2-9b-it","name":"Google: Gemma 2 9B","created":1719532800,"description":"Gemma 2 9B by Google is an advanced, open-source language model that sets a new standard for efficiency and performance in its size class.\n\nDesigned for a wide variety of tasks, it empowers developers and researchers to build innovative applications, while maintaining accessibility, safety, and cost-effectiveness.\n\nSee the [launch announcement](https://blog.google/technology/developers/google-gemma-2/) for more details. Usage of Gemma is subject to Google's [Gemma Terms of Use](https://ai.google.dev/gemma/terms).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Gemini","instruct_type":"gemma"},"pricing":{"prompt":"0.00000003","completion":"0.00000006","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"01-ai/yi-large","name":"01.AI: Yi Large","created":1719273600,"description":"The Yi Large model was designed by 01.AI with the following usecases in mind: knowledge search, data classification, human-like chat bots, and customer service.\n\nIt stands out for its multilingual proficiency, particularly in Spanish, Chinese, Japanese, German, and French.\n\nCheck out the [launch announcement](https://01-ai.github.io/blog/01.ai-yi-large-llm-launch) to learn more.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Yi","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000003","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"ai21/jamba-instruct","name":"AI21: Jamba Instruct","created":1719273600,"description":"The Jamba-Instruct model, introduced by AI21 Labs, is an instruction-tuned variant of their hybrid SSM-Transformer Jamba model, specifically optimized for enterprise applications.\n\n- 256K Context Window: It can process extensive information, equivalent to a 400-page novel, which is beneficial for tasks involving large documents such as financial reports or legal documents\n- Safety and Accuracy: Jamba-Instruct is designed with enhanced safety features to ensure secure deployment in enterprise environments, reducing the risk and cost of implementation\n\nRead their [announcement](https://www.ai21.com/blog/announcing-jamba) to learn more.\n\nJamba has a knowledge cutoff of February 2024.","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000005","completion":"0.0000007","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"anthropic/claude-3.5-sonnet-20240620:beta","name":"Anthropic: Claude 3.5 Sonnet (2024-06-20) (self-moderated)","created":1718841600,"description":"Claude 3.5 Sonnet delivers better-than-Opus capabilities, faster-than-Sonnet speeds, at the same Sonnet prices. 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This model is a finetune of [Mixtral 8x22B Instruct](/models/mistralai/mixtral-8x22b-instruct). It features a 64k context length and was fine-tuned with a 16k sequence length using ChatML templates.\n\nThis model is a successor to [Dolphin Mixtral 8x7B](/models/cognitivecomputations/dolphin-mixtral-8x7b).\n\nThe model is uncensored and is stripped of alignment and bias. It requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at [erichartford.com/uncensored-models](https://erichartford.com/uncensored-models).\n\n#moe #uncensored","context_length":16000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"chatml"},"pricing":{"prompt":"0.0000009","completion":"0.0000009","image":"0","request":"0"},"top_provider":{"context_length":16000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2-72b-instruct","name":"Qwen 2 72B Instruct","created":1717718400,"description":"Qwen2 72B is a transformer-based model that excels in language understanding, multilingual capabilities, coding, mathematics, and reasoning.\n\nIt features SwiGLU activation, attention QKV bias, and group query attention. 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It works best with English language inputs.\n\nFor more information, please see [Phi-4 Technical Report](https://arxiv.org/pdf/2412.08905)\n","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.00000007","completion":"0.00000014","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"sao10k/l3.1-70b-hanami-x1","name":"Sao10K: Llama 3.1 70B Hanami x1","created":1736302854,"description":"This is [Sao10K](/sao10k)'s experiment over [Euryale v2.2](/sao10k/l3.1-euryale-70b).","context_length":16000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000003","image":"0","request":"0"},"top_provider":{"context_length":16000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"deepseek/deepseek-chat","name":"DeepSeek: DeepSeek V3","created":1735241320,"description":"DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. 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Users should exercise caution when deploying this model.\n4. **Performance and Benchmark Limitations:** Despite the improvements in visual reasoning, QVQ doesn’t entirely replace the capabilities of [Qwen2-VL-72B](/qwen/qwen-2-vl-72b-instruct). During multi-step visual reasoning, the model might gradually lose focus on the image content, leading to hallucinations. Moreover, QVQ doesn’t show significant improvement over [Qwen2-VL-72B](/qwen/qwen-2-vl-72b-instruct) in basic recognition tasks like identifying people, animals, or plants.\n\nNote: Currently, the model only supports single-round dialogues and image outputs. 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Sloppy chats output were purged.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.000003375","completion":"0.0000045","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","created":1729555200,"description":"This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet(https://openrouter.ai/anthropic/claude-3.5-sonnet) and Opus(https://openrouter.ai/anthropic/claude-3-opus).\n\nThe model is fine-tuned on top of [Qwen2.5 72B](https://openrouter.ai/qwen/qwen-2.5-72b-instruct).","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000001875","completion":"0.00000225","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":1024,"is_moderated":false},"per_request_limits":null},{"id":"anthropic/claude-3.5-sonnet:beta","name":"Anthropic: Claude 3.5 Sonnet (self-moderated)","created":1729555200,"description":"New Claude 3.5 Sonnet delivers better-than-Opus capabilities, faster-than-Sonnet speeds, at the same Sonnet prices. 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Sonnet is particularly good at:\n\n- Coding: Scores ~49% on SWE-Bench Verified, higher than the last best score, and without any fancy prompt scaffolding\n- Data science: Augments human data science expertise; navigates unstructured data while using multiple tools for insights\n- Visual processing: excelling at interpreting charts, graphs, and images, accurately transcribing text to derive insights beyond just the text alone\n- Agentic tasks: exceptional tool use, making it great at agentic tasks (i.e. complex, multi-step problem solving tasks that require engaging with other systems)\n\n#multimodal","context_length":200000,"architecture":{"modality":"text+image->text","tokenizer":"Claude","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000015","image":"0.0048","request":"0"},"top_provider":{"context_length":200000,"max_completion_tokens":8192,"is_moderated":true},"per_request_limits":null},{"id":"x-ai/grok-beta","name":"xAI: Grok Beta","created":1729382400,"description":"Grok Beta is xAI's experimental language model with state-of-the-art reasoning capabilities, best for complex and multi-step use cases.\n\nIt is the successor of [Grok 2](https://x.ai/blog/grok-2) with enhanced context length.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Grok","instruct_type":null},"pricing":{"prompt":"0.000005","completion":"0.000015","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/ministral-8b","name":"Mistral: Ministral 8B","created":1729123200,"description":"Ministral 8B is an 8B parameter model featuring a unique interleaved sliding-window attention pattern for faster, memory-efficient inference. Designed for edge use cases, it supports up to 128k context length and excels in knowledge and reasoning tasks. It outperforms peers in the sub-10B category, making it perfect for low-latency, privacy-first applications.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.0000001","completion":"0.0000001","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/ministral-3b","name":"Mistral: Ministral 3B","created":1729123200,"description":"Ministral 3B is a 3B parameter model optimized for on-device and edge computing. It excels in knowledge, commonsense reasoning, and function-calling, outperforming larger models like Mistral 7B on most benchmarks. Supporting up to 128k context length, it’s ideal for orchestrating agentic workflows and specialist tasks with efficient inference.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.00000004","completion":"0.00000004","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2.5-7b-instruct","name":"Qwen2.5 7B Instruct","created":1729036800,"description":"Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2:\n\n- Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains.\n\n- Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots.\n\n- Long-context Support up to 128K tokens and can generate up to 8K tokens.\n\n- Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000000025","completion":"0.00000005","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"nvidia/llama-3.1-nemotron-70b-instruct:free","name":"NVIDIA: Llama 3.1 Nemotron 70B Instruct (free)","created":1728950400,"description":"NVIDIA's Llama 3.1 Nemotron 70B is a language model designed for generating precise and useful responses. Leveraging [Llama 3.1 70B](/models/meta-llama/llama-3.1-70b-instruct) architecture and Reinforcement Learning from Human Feedback (RLHF), it excels in automatic alignment benchmarks. This model is tailored for applications requiring high accuracy in helpfulness and response generation, suitable for diverse user queries across multiple domains.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"nvidia/llama-3.1-nemotron-70b-instruct","name":"NVIDIA: Llama 3.1 Nemotron 70B Instruct","created":1728950400,"description":"NVIDIA's Llama 3.1 Nemotron 70B is a language model designed for generating precise and useful responses. Leveraging [Llama 3.1 70B](/models/meta-llama/llama-3.1-70b-instruct) architecture and Reinforcement Learning from Human Feedback (RLHF), it excels in automatic alignment benchmarks. This model is tailored for applications requiring high accuracy in helpfulness and response generation, suitable for diverse user queries across multiple domains.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000012","completion":"0.0000003","image":"0","request":"0"},"top_provider":{"context_length":131000,"max_completion_tokens":131000,"is_moderated":false},"per_request_limits":null},{"id":"inflection/inflection-3-pi","name":"Inflection: Inflection 3 Pi","created":1728604800,"description":"Inflection 3 Pi powers Inflection's [Pi](https://pi.ai) chatbot, including backstory, emotional intelligence, productivity, and safety. It has access to recent news, and excels in scenarios like customer support and roleplay.\n\nPi has been trained to mirror your tone and style, if you use more emojis, so will Pi! Try experimenting with various prompts and conversation styles.","context_length":8000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000025","completion":"0.00001","image":"0","request":"0"},"top_provider":{"context_length":8000,"max_completion_tokens":1024,"is_moderated":false},"per_request_limits":null},{"id":"inflection/inflection-3-productivity","name":"Inflection: Inflection 3 Productivity","created":1728604800,"description":"Inflection 3 Productivity is optimized for following instructions. It is better for tasks requiring JSON output or precise adherence to provided guidelines. It has access to recent news.\n\nFor emotional intelligence similar to Pi, see [Inflect 3 Pi](/inflection/inflection-3-pi)\n\nSee [Inflection's announcement](https://inflection.ai/blog/enterprise) for more details.","context_length":8000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000025","completion":"0.00001","image":"0","request":"0"},"top_provider":{"context_length":8000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-flash-1.5-8b","name":"Google: Gemini Flash 1.5 8B","created":1727913600,"description":"Gemini Flash 1.5 8B is optimized for speed and efficiency, offering enhanced performance in small prompt tasks like chat, transcription, and translation. With reduced latency, it is highly effective for real-time and large-scale operations. This model focuses on cost-effective solutions while maintaining high-quality results.\n\n[Click here to learn more about this model](https://developers.googleblog.com/en/gemini-15-flash-8b-is-now-generally-available-for-use/).\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).","context_length":1000000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0.0000000375","completion":"0.00000015","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"anthracite-org/magnum-v2-72b","name":"Magnum v2 72B","created":1727654400,"description":"From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the seventh in a family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.\n\nThe model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000003","completion":"0.000003","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"liquid/lfm-40b","name":"Liquid: LFM 40B MoE","created":1727654400,"description":"Liquid's 40.3B Mixture of Experts (MoE) model. Liquid Foundation Models (LFMs) are large neural networks built with computational units rooted in dynamic systems.\n\nLFMs are general-purpose AI models that can be used to model any kind of sequential data, including video, audio, text, time series, and signals.\n\nSee the [launch announcement](https://www.liquid.ai/liquid-foundation-models) for benchmarks and more info.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":"chatml"},"pricing":{"prompt":"0.00000015","completion":"0.00000015","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"thedrummer/rocinante-12b","name":"Rocinante 12B","created":1727654400,"description":"Rocinante 12B is designed for engaging storytelling and rich prose.\n\nEarly testers have reported:\n- Expanded vocabulary with unique and expressive word choices\n- Enhanced creativity for vivid narratives\n- Adventure-filled and captivating stories","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.00000025","completion":"0.0000005","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-3b-instruct:free","name":"Meta: Llama 3.2 3B Instruct (free)","created":1727222400,"description":"Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages.\n\nTrained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":4096,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-3b-instruct","name":"Meta: Llama 3.2 3B Instruct","created":1727222400,"description":"Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages.\n\nTrained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.000000015","completion":"0.000000025","image":"0","request":"0"},"top_provider":{"context_length":131000,"max_completion_tokens":131000,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-1b-instruct:free","name":"Meta: Llama 3.2 1B Instruct (free)","created":1727222400,"description":"Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance.\n\nSupporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":4096,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-1b-instruct","name":"Meta: Llama 3.2 1B Instruct","created":1727222400,"description":"Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance.\n\nSupporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000001","completion":"0.00000001","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-90b-vision-instruct:free","name":"Meta: Llama 3.2 90B Vision Instruct (free)","created":1727222400,"description":"The Llama 90B Vision model is a top-tier, 90-billion-parameter multimodal model designed for the most challenging visual reasoning and language tasks. It offers unparalleled accuracy in image captioning, visual question answering, and advanced image-text comprehension. Pre-trained on vast multimodal datasets and fine-tuned with human feedback, the Llama 90B Vision is engineered to handle the most demanding image-based AI tasks.\n\nThis model is perfect for industries requiring cutting-edge multimodal AI capabilities, particularly those dealing with complex, real-time visual and textual analysis.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":4096,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-90b-vision-instruct","name":"Meta: Llama 3.2 90B Vision Instruct","created":1727222400,"description":"The Llama 90B Vision model is a top-tier, 90-billion-parameter multimodal model designed for the most challenging visual reasoning and language tasks. It offers unparalleled accuracy in image captioning, visual question answering, and advanced image-text comprehension. Pre-trained on vast multimodal datasets and fine-tuned with human feedback, the Llama 90B Vision is engineered to handle the most demanding image-based AI tasks.\n\nThis model is perfect for industries requiring cutting-edge multimodal AI capabilities, particularly those dealing with complex, real-time visual and textual analysis.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000009","completion":"0.0000009","image":"0.001301","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-11b-vision-instruct:free","name":"Meta: Llama 3.2 11B Vision Instruct (free)","created":1727222400,"description":"Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis.\n\nIts ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.2-11b-vision-instruct","name":"Meta: Llama 3.2 11B Vision Instruct","created":1727222400,"description":"Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis.\n\nIts ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text+image->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.000000055","completion":"0.000000055","image":"0.00007948","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B Instruct","created":1726704000,"description":"Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2:\n\n- Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains.\n\n- Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots.\n\n- Long-context Support up to 128K tokens and can generate up to 8K tokens.\n\n- Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.00000023","completion":"0.0000004","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2-vl-72b-instruct","name":"Qwen2-VL 72B Instruct","created":1726617600,"description":"Qwen2 VL 72B is a multimodal LLM from the Qwen Team with the following key enhancements:\n\n- SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc.\n\n- Understanding videos of 20min+: Qwen2-VL can understand videos over 20 minutes for high-quality video-based question answering, dialog, content creation, etc.\n\n- Agent that can operate your mobiles, robots, etc.: with the abilities of complex reasoning and decision making, Qwen2-VL can be integrated with devices like mobile phones, robots, etc., for automatic operation based on visual environment and text instructions.\n\n- Multilingual Support: to serve global users, besides English and Chinese, Qwen2-VL now supports the understanding of texts in different languages inside images, including most European languages, Japanese, Korean, Arabic, Vietnamese, etc.\n\nFor more details, see this [blog post](https://qwenlm.github.io/blog/qwen2-vl/) and [GitHub repo](https://github.com/QwenLM/Qwen2-VL).\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":4096,"architecture":{"modality":"text+image->text","tokenizer":"Qwen","instruct_type":null},"pricing":{"prompt":"0.0000004","completion":"0.0000004","image":"0.000578","request":"0"},"top_provider":{"context_length":4096,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"neversleep/llama-3.1-lumimaid-8b","name":"NeverSleep: Lumimaid v0.2 8B","created":1726358400,"description":"Lumimaid v0.2 8B is a finetune of [Llama 3.1 8B](/models/meta-llama/llama-3.1-8b-instruct) with a \"HUGE step up dataset wise\" compared to Lumimaid v0.1. Sloppy chats output were purged.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000001875","completion":"0.000001125","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"openai/o1-mini-2024-09-12","name":"OpenAI: o1-mini (2024-09-12)","created":1726099200,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.0000011","completion":"0.0000044","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":65536,"is_moderated":true},"per_request_limits":null},{"id":"openai/o1-preview","name":"OpenAI: o1-preview","created":1726099200,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.000015","completion":"0.00006","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":32768,"is_moderated":true},"per_request_limits":null},{"id":"openai/o1-preview-2024-09-12","name":"OpenAI: o1-preview (2024-09-12)","created":1726099200,"description":"The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. 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Learn more in the [launch announcement](https://openai.com/o1).\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.0000011","completion":"0.0000044","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":65536,"is_moderated":true},"per_request_limits":null},{"id":"mistralai/pixtral-12b","name":"Mistral: Pixtral 12B","created":1725926400,"description":"The first multi-modal, text+image-to-text model from Mistral AI. 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It is the successor of [Euryale L3 70B v2.1](/models/sao10k/l3-euryale-70b).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000007","completion":"0.0000008","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-flash-1.5-8b-exp","name":"Google: Gemini Flash 1.5 8B Experimental","created":1724803200,"description":"Gemini Flash 1.5 8B Experimental is an experimental, 8B parameter version of the [Gemini Flash 1.5](/models/google/gemini-flash-1.5) model.\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).\n\n#multimodal\n\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.","context_length":1000000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"ai21/jamba-1-5-large","name":"AI21: Jamba 1.5 Large","created":1724371200,"description":"Jamba 1.5 Large is part of AI21's new family of open models, offering superior speed, efficiency, and quality.\n\nIt features a 256K effective context window, the longest among open models, enabling improved performance on tasks like document summarization and analysis.\n\nBuilt on a novel SSM-Transformer architecture, it outperforms larger models like Llama 3.1 70B on benchmarks while maintaining resource efficiency.\n\nRead their [announcement](https://www.ai21.com/blog/announcing-jamba-model-family) to learn more.","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.000002","completion":"0.000008","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"ai21/jamba-1-5-mini","name":"AI21: Jamba 1.5 Mini","created":1724371200,"description":"Jamba 1.5 Mini is the world's first production-grade Mamba-based model, combining SSM and Transformer architectures for a 256K context window and high efficiency.\n\nIt works with 9 languages and can handle various writing and analysis tasks as well as or better than similar small models.\n\nThis model uses less computer memory and works faster with longer texts than previous designs.\n\nRead their [announcement](https://www.ai21.com/blog/announcing-jamba-model-family) to learn more.","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000002","completion":"0.0000004","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"microsoft/phi-3.5-mini-128k-instruct","name":"Microsoft: Phi-3.5 Mini 128K Instruct","created":1724198400,"description":"Phi-3.5 models are lightweight, state-of-the-art open models. 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It is recommended for people wanting more variety than Magnum, and yet more verbose prose than Celeste.","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"chatml"},"pricing":{"prompt":"0.0000008","completion":"0.0000012","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"openai/gpt-4o-2024-08-06","name":"OpenAI: GPT-4o (2024-08-06)","created":1722902400,"description":"The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format. Read more [here](https://openai.com/index/introducing-structured-outputs-in-the-api/).\n\nGPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.\n\nFor benchmarking against other models, it was briefly called [\"im-also-a-good-gpt2-chatbot\"](https://twitter.com/LiamFedus/status/1790064963966370209)","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.0000025","completion":"0.00001","image":"0.003613","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":16384,"is_moderated":true},"per_request_limits":null},{"id":"meta-llama/llama-3.1-405b","name":"Meta: Llama 3.1 405B (base)","created":1722556800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This is the base 405B pre-trained version.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"none"},"pricing":{"prompt":"0.000002","completion":"0.000002","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"nothingiisreal/mn-celeste-12b","name":"Mistral Nemo 12B Celeste","created":1722556800,"description":"A specialized story writing and roleplaying model based on Mistral's NeMo 12B Instruct. 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It demonstrates remarkable versatility in both SFW and NSFW scenarios, with strong Out of Character (OOC) steering capabilities, allowing fine-tuned control over narrative direction and character behavior.\n\nCheck out the model's [HuggingFace page](https://huggingface.co/nothingiisreal/MN-12B-Celeste-V1.9) for details on what parameters and prompts work best!","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"chatml"},"pricing":{"prompt":"0.0000008","completion":"0.0000012","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-small-128k-chat","name":"Perplexity: Llama 3.1 Sonar 8B","created":1722470400,"description":"Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is a normal offline LLM, but the [online version](/models/perplexity/llama-3.1-sonar-small-128k-online) of this model has Internet access.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.0000002","completion":"0.0000002","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-pro-1.5-exp","name":"Google: Gemini Pro 1.5 Experimental","created":1722470400,"description":"Gemini 1.5 Pro Experimental is a bleeding-edge version of the [Gemini 1.5 Pro](/models/google/gemini-pro-1.5) model. Because it's currently experimental, it will be **heavily rate-limited** by Google.\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).\n\n#multimodal","context_length":1000000,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":1000000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-large-128k-chat","name":"Perplexity: Llama 3.1 Sonar 70B","created":1722470400,"description":"Llama 3.1 Sonar is Perplexity's latest model family. 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It is focused on delivering helpful, up-to-date, and factual responses. #online","context_length":127072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.000001","completion":"0.000001","image":"0","request":"0.005"},"top_provider":{"context_length":127072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"perplexity/llama-3.1-sonar-small-128k-online","name":"Perplexity: Llama 3.1 Sonar 8B Online","created":1722470400,"description":"Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is the online version of the [offline chat model](/models/perplexity/llama-3.1-sonar-small-128k-chat). It is focused on delivering helpful, up-to-date, and factual responses. #online","context_length":127072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":null},"pricing":{"prompt":"0.0000002","completion":"0.0000002","image":"0","request":"0.005"},"top_provider":{"context_length":127072,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-405b-instruct:free","name":"Meta: Llama 3.1 405B Instruct (free)","created":1721692800,"description":"The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. 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Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000008","completion":"0.0000008","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-405b-instruct:nitro","name":"Meta: Llama 3.1 405B Instruct (nitro)","created":1721692800,"description":"The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":8000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00001462","completion":"0.00001462","image":"0","request":"0"},"top_provider":{"context_length":8000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-8b-instruct:free","name":"Meta: Llama 3.1 8B Instruct (free)","created":1721692800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-8b-instruct","name":"Meta: Llama 3.1 8B Instruct","created":1721692800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000002","completion":"0.00000005","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-8b-instruct:nitro","name":"Meta: Llama 3.1 8B Instruct (nitro)","created":1721692800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. 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This 70B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-70b-instruct","name":"Meta: Llama 3.1 70B Instruct","created":1721692800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000012","completion":"0.0000003","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"meta-llama/llama-3.1-70b-instruct:nitro","name":"Meta: Llama 3.1 70B Instruct (nitro)","created":1721692800,"description":"Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":64000,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.00000325","completion":"0.00000325","image":"0","request":"0"},"top_provider":{"context_length":64000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/mistral-nemo","name":"Mistral: Mistral Nemo","created":1721347200,"description":"A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA.\n\nThe model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.\n\nIt supports function calling and is released under the Apache 2.0 license.","context_length":131072,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"mistral"},"pricing":{"prompt":"0.000000035","completion":"0.00000008","image":"0","request":"0"},"top_provider":{"context_length":131072,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"mistralai/codestral-mamba","name":"Mistral: Codestral Mamba","created":1721347200,"description":"A 7.3B parameter Mamba-based model designed for code and reasoning tasks.\n\n- Linear time inference, allowing for theoretically infinite sequence lengths\n- 256k token context window\n- Optimized for quick responses, especially beneficial for code productivity\n- Performs comparably to state-of-the-art transformer models in code and reasoning tasks\n- Available under the Apache 2.0 license for free use, modification, and distribution","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.00000025","completion":"0.00000025","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"openai/gpt-4o-mini","name":"OpenAI: GPT-4o-mini","created":1721260800,"description":"GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.\n\nAs their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than [GPT-3.5 Turbo](/models/openai/gpt-3.5-turbo). It maintains SOTA intelligence, while being significantly more cost-effective.\n\nGPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences [common leaderboards](https://arena.lmsys.org/).\n\nCheck out the [launch announcement](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/) to learn more.\n\n#multimodal","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.00000015","completion":"0.0000006","image":"0.007225","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":16384,"is_moderated":true},"per_request_limits":null},{"id":"openai/gpt-4o-mini-2024-07-18","name":"OpenAI: GPT-4o-mini (2024-07-18)","created":1721260800,"description":"GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.\n\nAs their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than [GPT-3.5 Turbo](/models/openai/gpt-3.5-turbo). It maintains SOTA intelligence, while being significantly more cost-effective.\n\nGPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences [common leaderboards](https://arena.lmsys.org/).\n\nCheck out the [launch announcement](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/) to learn more.\n\n#multimodal","context_length":128000,"architecture":{"modality":"text+image->text","tokenizer":"GPT","instruct_type":null},"pricing":{"prompt":"0.00000015","completion":"0.0000006","image":"0.007225","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":16384,"is_moderated":true},"per_request_limits":null},{"id":"qwen/qwen-2-7b-instruct:free","name":"Qwen 2 7B Instruct (free)","created":1721088000,"description":"Qwen2 7B is a transformer-based model that excels in language understanding, multilingual capabilities, coding, mathematics, and reasoning.\n\nIt features SwiGLU activation, attention QKV bias, and group query attention. It is pretrained on extensive data with supervised finetuning and direct preference optimization.\n\nFor more details, see this [blog post](https://qwenlm.github.io/blog/qwen2/) and [GitHub repo](https://github.com/QwenLM/Qwen2).\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2-7b-instruct","name":"Qwen 2 7B Instruct","created":1721088000,"description":"Qwen2 7B is a transformer-based model that excels in language understanding, multilingual capabilities, coding, mathematics, and reasoning.\n\nIt features SwiGLU activation, attention QKV bias, and group query attention. It is pretrained on extensive data with supervised finetuning and direct preference optimization.\n\nFor more details, see this [blog post](https://qwenlm.github.io/blog/qwen2/) and [GitHub repo](https://github.com/QwenLM/Qwen2).\n\nUsage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000000054","completion":"0.000000054","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemma-2-27b-it","name":"Google: Gemma 2 27B","created":1720828800,"description":"Gemma 2 27B by Google is an open model built from the same research and technology used to create the [Gemini models](/models?q=gemini).\n\nGemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning.\n\nSee the [launch announcement](https://blog.google/technology/developers/google-gemma-2/) for more details. Usage of Gemma is subject to Google's [Gemma Terms of Use](https://ai.google.dev/gemma/terms).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Gemini","instruct_type":"gemma"},"pricing":{"prompt":"0.00000027","completion":"0.00000027","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"alpindale/magnum-72b","name":"Magnum 72B","created":1720656000,"description":"From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the first in a new family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.\n\nThe model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.","context_length":16384,"architecture":{"modality":"text->text","tokenizer":"Qwen","instruct_type":"chatml"},"pricing":{"prompt":"0.000001875","completion":"0.00000225","image":"0","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":1024,"is_moderated":false},"per_request_limits":null},{"id":"google/gemma-2-9b-it:free","name":"Google: Gemma 2 9B (free)","created":1719532800,"description":"Gemma 2 9B by Google is an advanced, open-source language model that sets a new standard for efficiency and performance in its size class.\n\nDesigned for a wide variety of tasks, it empowers developers and researchers to build innovative applications, while maintaining accessibility, safety, and cost-effectiveness.\n\nSee the [launch announcement](https://blog.google/technology/developers/google-gemma-2/) for more details. Usage of Gemma is subject to Google's [Gemma Terms of Use](https://ai.google.dev/gemma/terms).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Gemini","instruct_type":"gemma"},"pricing":{"prompt":"0","completion":"0","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"google/gemma-2-9b-it","name":"Google: Gemma 2 9B","created":1719532800,"description":"Gemma 2 9B by Google is an advanced, open-source language model that sets a new standard for efficiency and performance in its size class.\n\nDesigned for a wide variety of tasks, it empowers developers and researchers to build innovative applications, while maintaining accessibility, safety, and cost-effectiveness.\n\nSee the [launch announcement](https://blog.google/technology/developers/google-gemma-2/) for more details. Usage of Gemma is subject to Google's [Gemma Terms of Use](https://ai.google.dev/gemma/terms).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Gemini","instruct_type":"gemma"},"pricing":{"prompt":"0.00000003","completion":"0.00000006","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"01-ai/yi-large","name":"01.AI: Yi Large","created":1719273600,"description":"The Yi Large model was designed by 01.AI with the following usecases in mind: knowledge search, data classification, human-like chat bots, and customer service.\n\nIt stands out for its multilingual proficiency, particularly in Spanish, Chinese, Japanese, German, and French.\n\nCheck out the [launch announcement](https://01-ai.github.io/blog/01.ai-yi-large-llm-launch) to learn more.","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Yi","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000003","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"ai21/jamba-instruct","name":"AI21: Jamba Instruct","created":1719273600,"description":"The Jamba-Instruct model, introduced by AI21 Labs, is an instruction-tuned variant of their hybrid SSM-Transformer Jamba model, specifically optimized for enterprise applications.\n\n- 256K Context Window: It can process extensive information, equivalent to a 400-page novel, which is beneficial for tasks involving large documents such as financial reports or legal documents\n- Safety and Accuracy: Jamba-Instruct is designed with enhanced safety features to ensure secure deployment in enterprise environments, reducing the risk and cost of implementation\n\nRead their [announcement](https://www.ai21.com/blog/announcing-jamba) to learn more.\n\nJamba has a knowledge cutoff of February 2024.","context_length":256000,"architecture":{"modality":"text->text","tokenizer":"Other","instruct_type":null},"pricing":{"prompt":"0.0000005","completion":"0.0000007","image":"0","request":"0"},"top_provider":{"context_length":256000,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"anthropic/claude-3.5-sonnet-20240620:beta","name":"Anthropic: Claude 3.5 Sonnet (2024-06-20) (self-moderated)","created":1718841600,"description":"Claude 3.5 Sonnet delivers better-than-Opus capabilities, faster-than-Sonnet speeds, at the same Sonnet prices. Sonnet is particularly good at:\n\n- Coding: Autonomously writes, edits, and runs code with reasoning and troubleshooting\n- Data science: Augments human data science expertise; navigates unstructured data while using multiple tools for insights\n- Visual processing: excelling at interpreting charts, graphs, and images, accurately transcribing text to derive insights beyond just the text alone\n- Agentic tasks: exceptional tool use, making it great at agentic tasks (i.e. complex, multi-step problem solving tasks that require engaging with other systems)\n\nFor the latest version (2024-10-23), check out [Claude 3.5 Sonnet](/anthropic/claude-3.5-sonnet).\n\n#multimodal","context_length":200000,"architecture":{"modality":"text+image->text","tokenizer":"Claude","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000015","image":"0.0048","request":"0"},"top_provider":{"context_length":200000,"max_completion_tokens":8192,"is_moderated":false},"per_request_limits":null},{"id":"anthropic/claude-3.5-sonnet-20240620","name":"Anthropic: Claude 3.5 Sonnet (2024-06-20)","created":1718841600,"description":"Claude 3.5 Sonnet delivers better-than-Opus capabilities, faster-than-Sonnet speeds, at the same Sonnet prices. Sonnet is particularly good at:\n\n- Coding: Autonomously writes, edits, and runs code with reasoning and troubleshooting\n- Data science: Augments human data science expertise; navigates unstructured data while using multiple tools for insights\n- Visual processing: excelling at interpreting charts, graphs, and images, accurately transcribing text to derive insights beyond just the text alone\n- Agentic tasks: exceptional tool use, making it great at agentic tasks (i.e. complex, multi-step problem solving tasks that require engaging with other systems)\n\nFor the latest version (2024-10-23), check out [Claude 3.5 Sonnet](/anthropic/claude-3.5-sonnet).\n\n#multimodal","context_length":200000,"architecture":{"modality":"text+image->text","tokenizer":"Claude","instruct_type":null},"pricing":{"prompt":"0.000003","completion":"0.000015","image":"0.0048","request":"0"},"top_provider":{"context_length":200000,"max_completion_tokens":8192,"is_moderated":true},"per_request_limits":null},{"id":"sao10k/l3-euryale-70b","name":"Sao10k: Llama 3 Euryale 70B v2.1","created":1718668800,"description":"Euryale 70B v2.1 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k).\n\n- Better prompt adherence.\n- Better anatomy / spatial awareness.\n- Adapts much better to unique and custom formatting / reply formats.\n- Very creative, lots of unique swipes.\n- Is not restrictive during roleplays.","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"llama3"},"pricing":{"prompt":"0.0000007","completion":"0.0000008","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":4096,"is_moderated":false},"per_request_limits":null},{"id":"cognitivecomputations/dolphin-mixtral-8x22b","name":"Dolphin 2.9.2 Mixtral 8x22B 🐬","created":1717804800,"description":"Dolphin 2.9 is designed for instruction following, conversational, and coding. This model is a finetune of [Mixtral 8x22B Instruct](/models/mistralai/mixtral-8x22b-instruct). It features a 64k context length and was fine-tuned with a 16k sequence length using ChatML templates.\n\nThis model is a successor to [Dolphin Mixtral 8x7B](/models/cognitivecomputations/dolphin-mixtral-8x7b).\n\nThe model is uncensored and is stripped of alignment and bias. It requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at [erichartford.com/uncensored-models](https://erichartford.com/uncensored-models).\n\n#moe #uncensored","context_length":16000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"chatml"},"pricing":{"prompt":"0.0000009","completion":"0.0000009","image":"0","request":"0"},"top_provider":{"context_length":16000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"qwen/qwen-2-72b-instruct","name":"Qwen 2 72B Instruct","created":1717718400,"description":"Qwen2 72B is a transformer-based model that excels in language understanding, multilingual capabilities, coding, mathematics, and reasoning.\n\nIt features SwiGLU activation, attention QKV bias, and group query attention. 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Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).","context_length":8192,"architecture":{"modality":"text->text","tokenizer":"Llama3","instruct_type":"none"},"pricing":{"prompt":"0.0000002","completion":"0.0000002","image":"0","request":"0"},"top_provider":{"context_length":8192,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"openai/gpt-4o","name":"OpenAI: GPT-4o","created":1715558400,"description":"GPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. 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Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/).\n\nIt supports dozens of languages including French, German, Spanish, Italian, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese, and Korean, along with 80+ coding languages including Python, Java, C, C++, JavaScript, and Bash. Its long context window allows precise information recall from large documents.","context_length":128000,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":null},"pricing":{"prompt":"0.000002","completion":"0.000006","image":"0","request":"0"},"top_provider":{"context_length":128000,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemma-7b-it","name":"Google: Gemma 7B","created":1708560000,"description":"Gemma by Google is an advanced, open-source language model family, leveraging the latest in decoder-only, text-to-text technology. 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Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at [erichartford.com/uncensored-models](https://erichartford.com/uncensored-models).\n\n#moe #uncensored","context_length":32768,"architecture":{"modality":"text->text","tokenizer":"Mistral","instruct_type":"chatml"},"pricing":{"prompt":"0.0000005","completion":"0.0000005","image":"0","request":"0"},"top_provider":{"context_length":32768,"max_completion_tokens":null,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-pro-vision","name":"Google: Gemini Pro Vision 1.0","created":1702425600,"description":"Google's flagship multimodal model, supporting image and video in text or chat prompts for a text or code response.\n\nSee the benchmarks and prompting guidelines from [Deepmind](https://deepmind.google/technologies/gemini/).\n\nUsage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms).\n\n#multimodal","context_length":16384,"architecture":{"modality":"text+image->text","tokenizer":"Gemini","instruct_type":null},"pricing":{"prompt":"0.0000005","completion":"0.0000015","image":"0.0025","request":"0"},"top_provider":{"context_length":16384,"max_completion_tokens":2048,"is_moderated":false},"per_request_limits":null},{"id":"google/gemini-pro","name":"Google: Gemini Pro 1.0","created":1702425600,"description":"Google's flagship text generation model. 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