diff --git a/Project.toml b/Project.toml
index ca4f6d76f..e9b1ac491 100644
--- a/Project.toml
+++ b/Project.toml
@@ -6,7 +6,7 @@ version = "1.18.1"
 [deps]
 ArrayInterfaceCore = "30b0a656-2188-435a-8636-2ec0e6a096e2"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
-GPUArrays = "0c68f7d7-f131-5f86-a1c3-88cf8149b2d7"
+GPUArraysCore = "46192b85-c4d5-4398-a991-12ede77f4527"
 IterativeSolvers = "42fd0dbc-a981-5370-80f2-aaf504508153"
 KLU = "ef3ab10e-7fda-4108-b977-705223b18434"
 Krylov = "ba0b0d4f-ebba-5204-a429-3ac8c609bfb7"
@@ -23,7 +23,7 @@ UnPack = "3a884ed6-31ef-47d7-9d2a-63182c4928ed"
 [compat]
 ArrayInterfaceCore = "0.1.1"
 DocStringExtensions = "0.8"
-GPUArrays = "8"
+GPUArraysCore = "0.1"
 IterativeSolvers = "0.9.2"
 KLU = "0.3.0"
 Krylov = "0.7.11, 0.8"
diff --git a/src/LinearSolve.jl b/src/LinearSolve.jl
index 16ace7803..1cb3ae379 100644
--- a/src/LinearSolve.jl
+++ b/src/LinearSolve.jl
@@ -14,7 +14,7 @@ using SuiteSparse
 using KLU
 using DocStringExtensions
 
-import GPUArrays
+import GPUArraysCore
 
 # wrap
 import Krylov
diff --git a/src/default.jl b/src/default.jl
index 68e06e816..301f201ae 100644
--- a/src/default.jl
+++ b/src/default.jl
@@ -9,7 +9,7 @@ function defaultalg(A,b)
     # Special case on Arrays: avoid BLAS for RecursiveFactorization.jl when
     # it makes sense according to the benchmarks, which is dependent on
     # whether MKL or OpenBLAS is being used
-    if (A === nothing && !(b isa GPUArrays.AbstractGPUArray)) || A isa Matrix
+    if (A === nothing && !(b isa GPUArraysCore.AbstractGPUArray)) || A isa Matrix
         if (A === nothing || eltype(A) <: Union{Float32,Float64,ComplexF32,ComplexF64}) &&
                     ArrayInterfaceCore.can_setindex(b)
             if length(b) <= 10
@@ -39,7 +39,7 @@ function defaultalg(A,b)
 
     # This catches the case where A is a CuMatrix
     # Which does not have LU fully defined
-    elseif A isa GPUArrays.AbstractGPUArray || b isa GPUArrays.AbstractGPUArray
+    elseif A isa GPUArraysCore.AbstractGPUArray || b isa GPUArraysCore.AbstractGPUArray
         alg = QRFactorization(false)
 
     # Not factorizable operator, default to only using A*x
@@ -100,7 +100,7 @@ function SciMLBase.solve(cache::LinearCache, alg::Nothing,
 
     # This catches the case where A is a CuMatrix
     # Which does not have LU fully defined
-    elseif A isa GPUArrays.AbstractGPUArray
+    elseif A isa GPUArraysCore.AbstractGPUArray
         alg = QRFactorization(false)
         SciMLBase.solve(cache, alg, args...; kwargs...)
 
@@ -158,7 +158,7 @@ function init_cacheval(alg::Nothing, A, b, u, Pl, Pr, maxiters, abstol, reltol,
 
     # This catches the case where A is a CuMatrix
     # Which does not have LU fully defined
-    elseif A isa GPUArrays.AbstractGPUArray
+    elseif A isa GPUArraysCore.AbstractGPUArray
         alg = QRFactorization(false)
         init_cacheval(alg, A, b, u, Pl, Pr, maxiters, abstol, reltol, verbose)