diff --git a/docs/src/solvers/solvers.md b/docs/src/solvers/solvers.md
index 7bcb11a56..286a5ead2 100644
--- a/docs/src/solvers/solvers.md
+++ b/docs/src/solvers/solvers.md
@@ -238,6 +238,19 @@ The following are non-standard GPU factorization routines.
 CudaOffloadFactorization
 ```
 
+### AMDGPU.jl
+
+The following are GPU factorization routines for AMD GPUs using the ROCm stack.
+
+!!! note
+    
+    Using these solvers requires adding the package AMDGPU.jl, i.e. `using AMDGPU`
+
+```@docs
+AMDGPUOffloadLUFactorization
+AMDGPUOffloadQRFactorization
+```
+
 ### CUSOLVERRF.jl
 
 !!! note
diff --git a/docs/src/tutorials/gpu.md b/docs/src/tutorials/gpu.md
index ee737668c..f348c647a 100644
--- a/docs/src/tutorials/gpu.md
+++ b/docs/src/tutorials/gpu.md
@@ -39,8 +39,18 @@ sol.u
 This computation can be moved to the GPU by the following:
 
 ```julia
-using CUDA # Add the GPU library
-sol = LS.solve(prob, LS.CudaOffloadFactorization())
+using CUDA # Add the GPU library for NVIDIA GPUs
+sol = LS.solve(prob, LS.CudaOffloadLUFactorization())
+sol.u
+```
+
+For AMD GPUs, you can use the AMDGPU.jl package:
+
+```julia
+using AMDGPU # Add the GPU library for AMD GPUs
+sol = LS.solve(prob, LS.AMDGPUOffloadLUFactorization())  # LU factorization
+# or
+sol = LS.solve(prob, LS.AMDGPUOffloadQRFactorization())  # QR factorization
 sol.u
 ```