QwenQwen 2.5 Coder 32B Instruct on NVIDIA Grace Blackwell Ultra GB300
Yes — Grace Blackwell Ultra GB300 runs Qwen 2.5 Coder 32B Instruct excellently at Q5_K_M — 140 tok/s. 288 GB VRAM with plenty of headroom.
Model Size
32.5B
Device VRAM
288 GB
Bandwidth
8000 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Qwen 2.5 Coder 32B Instruct on NVIDIA Grace Blackwell Ultra GB300 at Q5_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q5_K_M | 140 tok/s | 75ms | ✓ Yes | Excellent | estimated |
Notes
Q5_K_M
High quality code completion. 266GB headroom.
About Qwen 2.5 Coder 32B Instruct
Qwen 2.5 Coder 32B Instruct (32.5B) is a coding, ai coding, ai building model. The coding model that defines the builder workflow. Matches GPT-4 on HumanEval. This is what Cursor and Continue.dev users run locally when they want to eliminate API dependency. Apache 2.0 license. The cornerstone of the 'Full AI Builder' profile.
View all Qwen 2.5 Coder 32B Instruct hardware options →About NVIDIA Grace Blackwell Ultra GB300
NVIDIA Grace Blackwell Ultra GB300 has 288 GB at 8000 GB/s. Street price: $30,000.
See all models NVIDIA Grace Blackwell Ultra GB300 can run →Estimate method: Estimated from GB300 bandwidth ratio vs RTX 4090. Reference hardware source: dell.com (2026-03-23)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.