Intermediate 12 minOllama

Ollama + AMD GPU (ROCm): configure Radeon RX 6000 to 9000

AMD lagged behind CUDA for a long time, but ROCm 6 has caught up enough for Radeon RX 6000, 7000, and 9000 to be fully usable for LLM inference. This guide covers a clean installation, Ollama configuration, and the override that lets you run cards not officially listed.

By Mohamed Meguedmi·Update 2026-08-27·Tested on Windows, macOS, and Linux

#Why ROCm

To use an AMD GPU, Ollama (which relies on llama.cpp) must run through ROCm — AMD’s equivalent of CUDA. Without ROCm, the card is invisible to inference and everything runs on the CPU.

i
Alternative: Vulkan
If ROCm refuses to cooperate, llama.cpp compiled with Vulkan also works on AMD (and Intel Arc, for that matter). Slightly slower but simpler. See the llama.cpp guide with Vulkan.

#Officially compatible cards

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RX 7900 XTX / XT / GRE
gfx1100. Officially supported. About 80% of the performance of a RTX 4080.
RX 7800 / 7700 XT
gfx1101. Official support since ROCm 6.1.
RX 6900 / 6800 / 6700 XT
gfx1030/1031. Official support for large cards, override for smaller ones.
Instinct MI200 / MI300
Data center cards. Full native support.
!
RX 6600, 6500, 5700
Not officially supported. Anything is possible with the HSA_OVERRIDE_GFX_VERSION variable (see below), but at your own risk.

#1. Install ROCm

The two best-supported distributions are Ubuntu 22.04/24.04 and RHEL/Fedora. Debian, Arch, and similar distributions require additional workarounds.

Ubuntu 24.04
# Dépôt officiel
wget https://repo.radeon.com/amdgpu-install/6.1/ubuntu/noble/amdgpu-install_6.1.60100-1_all.deb
sudo apt install ./amdgpu-install_6.1.60100-1_all.deb

# ROCm + drivers GPU
sudo amdgpu-install --usecase=rocm,graphics

# Droits utilisateur
sudo usermod -aG render,video $USER

# Reboot obligatoire
sudo reboot
Post-reboot verification
rocminfo | grep gfx
# Doit afficher votre architecture, ex : gfx1100

rocm-smi
# Résumé VRAM, température, conso

#2. Ollama and ROCm

Ollama 0.3+ detects ROCm automatically. If you installed Ollama BEFORE ROCm, reinstall it—the script will then detect the AMD GPU and install the correct libraries.

Reinstall after ROCm
curl -fsSL https://ollama.com/install.sh | sh
systemctl restart ollama
Test
ollama run qwen3.5:9b "Test GPU"
# Puis dans un autre terminal :
rocm-smi --showuse
# La ligne GPU[0] doit bouger

#3. Force an unsupported card

If rocminfo does not list your GPU, or if Ollama continues to use the CPU, the HSA_OVERRIDE_GFX_VERSION variable forces ROCm to pretend.

RX 6600 / 6700
HSA_OVERRIDE_GFX_VERSION=10.3.0
RX 5700 XT
HSA_OVERRIDE_GFX_VERSION=10.1.0 (fragile support)
RX 6800 / 6900
Supported natively; no override needed.
In the Ollama systemd override
sudo systemctl edit ollama

# Ajouter :
[Service]
Environment="HSA_OVERRIDE_GFX_VERSION=10.3.0"

sudo systemctl daemon-reload
sudo systemctl restart ollama

#4. Expected performance

For Qwen 3.5 9B Q4_K_M (6.6 GB, the reference 8 GB choice in 2026), here are the approximate tokens-per-second figures during inference:

RX 7900 XTX (24 GB)
~90 tok/s. Comparable to a RTX 4080.
RX 7800 XT (16 GB)
~62 tok/s. Between RTX 4070 and 4070 Ti.
RX 6900 XT (16 GB)
~52 tok/s. Equivalent to RTX 3080 10 GB.
RX 6700 XT (12 GB, override)
~33 tok/s. Between RTX 3060 and 3060 Ti.
→
VRAM is king
On AMD as on NVIDIA, VRAM is what opens the door to large models. A RX 7900 XTX 24 GB can run Qwen 3.6 35B-A3B (23 GB in Q4), which a RTX 4070 12 GB cannot load, even though the 4070 is faster in raw compute.

#Troubleshooting

rocminfo is empty
Drivers not installed or user not in the render group. Check groups $USER.
Ollama uses the CPU despite ROCm
Often an architecture incompatibility. Try the HSA_OVERRIDE corresponding to the generation above.
Crash on large model (OOM)
Use rocm-smi to see how much VRAM is being used. If you exceed the limit, reduce num_ctx or switch to Q3_K_M.
Incompatible ROCm version Ollama
Ollama packaged for ROCm 6.x. ROCm 5 does not work. Update.
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