GPUs/AMD Radeon PRO W7900/Qwen 2.5 Coder 32B

Can AMD Radeon PRO W7900 run Qwen 2.5 Coder 32B?

32B parameter Code model on 48GB GDDR6 ECC

Yes — runs at 8-bit quantization
~11-13 tok/sSlow
SpeedFast inference, near-native speed
QualityNear-lossless — virtually identical to FP16
AMD GPUs lack CUDA. While Qwen 2.5 Coder 32B can technically run via llama.cpp/GGUF, the setup is more complex and less optimized than on NVIDIA hardware.

VRAM Requirements

Qwen 2.5 Coder 32B is a 32B parameter model. At full precision (FP16), it requires 64GB of VRAM. Your AMD Radeon PRO W7900 has 48GB, so you'll need to quantize it to 8-bit (Q8) to fit.

FP16 (Full Precision)64GB (need 16GB more)

Maximum quality, no quantization

Q8 (8-bit)32GB (16GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)20GB (28GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 48GB GDDR6 ECC at 864 GB/s bandwidth
Recommended system RAM: 96GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

Qwen 2.5 Coder 32B at this precision on AMD Radeon PRO W7900 gives excellent code completion and generation. Fast enough for real-time IDE integration. Handles complex refactoring, multi-file edits, and long-context code understanding.

How to Set It Up

Step 1: Install Ollama

curl -fsSL https://ollama.com/install.sh | sh

Ollama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.

Step 2: Download and run Qwen 2.5 Coder 32B

ollama run qwen2.5:32b

This downloads the model (~32GB). First run takes a few minutes.

Step 3: Verify GPU is being used

rocm-smi

Check that VRAM usage increases when the model loads. You should see ~32GB used.

AMD Radeon PRO W7900 Specs

VRAM48GB GDDR6 ECC
Memory Bandwidth864 GB/s
TDP295W
CUDA CoresN/A
Street Price~$3600
AI Rating6/10

Other Code Models on AMD Radeon PRO W7900

About Qwen 2.5 Coder 32B

Best open-source coding model. Needs 24GB+ for good quality.

Category: Code · Parameters: 32B · CUDA required: No (runs via llama.cpp/GGUF)