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[GH-ISSUE #12754] Title: ROCm GPU (RX 7900 XTX) Not Utilized on Windows 11 with iGPU Present - Fallback to CPU #54971
Closed
opened 2026-04-29 08:05:47 -05:00 by GiteaMirror
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Originally created by @AwarePL on GitHub (Oct 23, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/12754
Originally assigned to: @dhiltgen on GitHub.
What is the issue?
Environment:
OS: Windows 11 Professional (x64) Build 26100.6725
CPU: AMD Ryzen 9 7900X3D 12-Core Processor
GPU (Dedicated): AMD Radeon RX 7900 XTX (Navi 31 XTX, 24GB GDDR6)
GPU (Integrated): AMD Radeon Graphics (Raphael, 512MB shared)
RAM: 64 GB DDR5 @ 6000 MHz (EXPO enabled)
Motherboard: ASUS ROG CROSSHAIR X670E HERO
Ollama Version: 0.12.6 (as seen in logs)
AMD Driver Version: Adrenalin 25.9.1 (Clean install performed using DDU)
Steps to Reproduce:
Ensure Ollama is installed on a Windows system with both AMD integrated graphics and a dedicated AMD RDNA3 GPU (like RX 7900 XTX).
Open cmd as Administrator.
Stop the background Ollama service: net stop "Ollama Application"
Kill any remaining processes: taskkill /F /IM "ollama.exe" /T
Set environment variables to force dGPU usage and enable debugging. Attempts included various combinations, primarily:
set ROCR_VISIBLE_DEVICES=0
set HIP_VISIBLE_DEVICES=0 (Tried alone and in combination with ROCR_VISIBLE_DEVICES)
set OLLAMA_NUM_GPU=999 (To force loading layers)
set OLLAMA_DEBUG=1
Start the Ollama server in the same admin cmd window: ollama serve
Attempt to load and run any model (e.g., via ollama run ... in another terminal or through an API call). The model used in logs was hf.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF:UD-Q3_K_XL).
Expected Behavior:
Ollama should detect and select the AMD Radeon RX 7900 XTX (identified as id=0 library=ROCm compute=gfx1100 in logs) as the primary inference device.
It should recognize the available VRAM (approx. 21+ GiB available according to initial discovery logs).
When loading a model with OLLAMA_NUM_GPU=999, it should offload all or most model layers to the RX 7900 XTX VRAM (e.g., offloaded 49/49 layers to GPU).
Inference should primarily utilize the dGPU, minimizing CPU usage for heavy computation.
Actual Behavior:
The behavior slightly varied depending on the environment variables used, but consistently resulted in CPU-only operation:
With ROCR_VISIBLE_DEVICES=0 only (or initially):
Logs sometimes showed the correct initial intent (load request="{... GPULayers:49[ID:0 Layers:49(0..48)] ...}").
However, during the VRAM check phase for loading, it reported available layer vram"="0 B" and logged "insufficient VRAM to load any model layers".
It then fell back to CPU (new layout created layers=[]) and loaded 0 layers onto the GPU (offloaded 0/49 layers to GPU).
With HIP_VISIBLE_DEVICES=0 (alone or with ROCR_VISIBLE_DEVICES):
The GPU discovery process during startup failed to select the dGPU.
It immediately selected the CPU (inference compute id=cpu library=cpu).
It entered "low vram mode" (entering low vram mode "total vram"="0 B").
All subsequent model loads targeted the CPU (GPULayers:[]) and resulted in offloaded 0/49 layers to GPU.
In all tested scenarios, the model runs entirely on the CPU, utilizing significant system RAM instead of the dedicated GPU VRAM.
Logs:
Relevant DEBUG log excerpts demonstrating the issue (GPU detection failure / incorrect VRAM reporting / fallback to CPU) can be provided upon request. Key messages include: inference compute id=cpu entering low vram mode "total vram"="0 B" available layer vram"="0 B" insufficient VRAM to load any model layers offloaded 0/XX layers to GPU
Additional Context:
The integrated GPU (AMD Radeon Graphics on the 7900X3D) must remain enabled for other purposes and cannot be disabled in the BIOS/Device Manager as a workaround.
A clean installation of the latest recommended AMD Adrenalin drivers (25.9.1) using DDU was performed, but did not resolve the issue.
The issue seems related to GPU selection or VRAM reporting specifically within Ollama's ROCm integration on Windows when multiple AMD GPUs are present.
Relevant log output
OS
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GPU
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CPU
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Ollama version
No response
@dhiltgen commented on GitHub (Oct 23, 2025):
@AwarePL can you confirm if you do not set HIP_VISIBLE_DEVICES or ROCR_VISIBLE_DEVICES Ollama correctly discovers your discrete GPUs?
@AwarePL commented on GitHub (Oct 24, 2025):
It does, just does not use it ;)
here's log:
@ganakee commented on GitHub (Oct 24, 2025):
A similar issue appears with an AMD 6650 (10.3.0). Linux no longer sees the integrated GPU and falls-back to CPU with 0.12.6.
I temporarily re-installed 0.12.2.
nvtopon Linux shows the AMD GPU working fine in 0.12.2 but no GPU usage in 0.12.6. Same setup. Same config.As reported, perhaps ollama 0.12.6 does not seem to be seeing the environment variables--either from Linux
.bashrcnor in aollama.serviceviasystemd.I set
HIP_VISIBLE_DEVICESand/orROCR_VISIBLE_DEVICESin 12.6 with no apparent effect. (and also HFX OVERRIDE).@dhiltgen commented on GitHub (Oct 25, 2025):
I think the problem is likely related to IDs getting mixed up due to the iGPU being hidden. ROCm enumerates ID=0 as the iGPU, then ID=1 as the discrete GPU, but once we filter out the iGPU, the discrete becomes 0, and somewhere when we're looking VRAM info that is getting mapped back to the iGPU incorrectly. This might be fixed on main already, but I'll try to repro and confirm.
@AwarePL commented on GitHub (Oct 25, 2025):
downgrade to 0.12.3 solved it!
@ganakee commented on GitHub (Oct 29, 2025):
0.12.7-rc0 still broken.
The new 0.12.7-rc0 retains this issue for me on Linux and AMD 6650. The GPU is ignored in 0.12.7-rc0.
Downgraded to 0.12.2 to fix for me for now.
@dhiltgen commented on GitHub (Oct 29, 2025):
@ganakee sorry to hear that. Please share an updated log with OLLAMA_DEBUG=2 set so we can take a look.