diff --git a/src/fast_api_app/routes/infer.py b/src/fast_api_app/routes/infer.py
index d405924..48da42a 100644
--- a/src/fast_api_app/routes/infer.py
+++ b/src/fast_api_app/routes/infer.py
@@ -9,12 +9,18 @@
 from fastapi.responses import HTMLResponse
 from pydantic import BaseModel
 
-from fast_api_app.connections import limiter, model_queue, redis_conn, async_session
+from fast_api_app.connections import (
+    async_session,
+    limiter,
+    model_queue,
+    redis_conn,
+)
 from shared_lib.constants import (
     BUCKET_THRESHOLDS,
     MAIN_ONLY_ABILITIES,
     STANDARD_ABILITIES,
 )
+from shared_lib.models import ModelInferenceLog
 
 router = APIRouter()
 
@@ -298,29 +304,21 @@ async def log_inference_request(
                 )
             else:
                 async with async_session() as session:
-                    await session.execute(
-                        """
-                        INSERT INTO splatgpt.model_inference_logs (
-                            request_id, ip_address, user_agent, http_method,
-                            endpoint, input_data, model_version,
-                            processing_time_ms, status_code, error_message,
-                            output_data
-                        ) VALUES (
-                            $1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11
-                        )
-                    """,
-                        request_id,
-                        log_entry["ip_address"],
-                        log_entry["user_agent"],
-                        log_entry["http_method"],
-                        log_entry["endpoint"],
-                        log_entry["input_data"],
-                        log_entry["model_version"],
-                        log_entry["processing_time_ms"],
-                        log_entry["status_code"],
-                        log_entry["error_message"],
-                        log_entry.get("output_data"),
+                    new_log_entry = ModelInferenceLog(
+                        request_id=request_id,
+                        ip_address=log_entry["ip_address"],
+                        user_agent=log_entry["user_agent"],
+                        http_method=log_entry["http_method"],
+                        endpoint=log_entry["endpoint"],
+                        input_data=log_entry["input_data"],
+                        model_version=log_entry["model_version"],
+                        processing_time_ms=log_entry["processing_time_ms"],
+                        status_code=log_entry["status_code"],
+                        error_message=log_entry["error_message"],
+                        output_data=log_entry.get("output_data"),
                     )
+                    session.add(new_log_entry)
+                    await session.commit()
         except Exception as db_error:
             logger.error(f"Failed to log inference request: {db_error}")
 
diff --git a/src/shared_lib/models.py b/src/shared_lib/models.py
index 9cc5615..7e8d131 100644
--- a/src/shared_lib/models.py
+++ b/src/shared_lib/models.py
@@ -1,14 +1,21 @@
+import uuid
+
 from sqlalchemy import (
+    UUID,
+    BigInteger,
     Boolean,
     Column,
     DateTime,
     Float,
     Index,
     Integer,
+    SmallInteger,
     String,
+    Text,
     UniqueConstraint,
+    text,
 )
-from sqlalchemy.dialects.postgresql import ENUM
+from sqlalchemy.dialects.postgresql import ENUM, INET, JSONB
 from sqlalchemy.ext.declarative import declarative_base
 
 Base = declarative_base()
@@ -231,3 +238,25 @@ class WeaponLeaderboard(Base):
         Index("idx_weapon_leaderboard_weapon_id", "weapon_id"),
         {"schema": "xscraper"},
     )
+
+
+class ModelInferenceLog(Base):
+    __tablename__ = "model_inference_logs"
+    __table_args__ = {"schema": "splatgpt"}
+
+    id = Column(BigInteger, primary_key=True)
+    request_id = Column(UUID(as_uuid=True), default=uuid.uuid4)
+    timestamp = Column(
+        DateTime(timezone=True), server_default=text("CURRENT_TIMESTAMP")
+    )
+    ip_address = Column(INET)
+    user_agent = Column(Text)
+    http_method = Column(String)
+    endpoint = Column(String)
+    client_id = Column(String)
+    input_data = Column(JSONB)
+    model_version = Column(String)
+    processing_time_ms = Column(Integer)
+    status_code = Column(SmallInteger)
+    output_data = Column(JSONB)
+    error_message = Column(Text)