Qwen Qwen2 5 Coder 32B Instruct speed on NVIDIA RTX 6000 Ada and quantization-level VRAM fit.
NVIDIA RTX 6000 Ada meets the minimum VRAM requirement for Q4 inference of Qwen Qwen2 5 Coder 32B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA RTX 6000 Ada can run Qwen Qwen2 5 Coder 32B Instruct with Q4 quantization. At approximately 62 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 32GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 16GB | 48GB | 62.47 tok/s | ✅ Fits comfortably |
| Q8 | 32GB | 48GB | 43.73 tok/s | ✅ Fits comfortably |
| FP16 | 64GB | 48GB | 23.74 tok/s | ❌ Not recommended |
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NVIDIA RTX 6000 Ada can run Qwen Qwen2 5 Coder 32B Instruct at Q4 with an estimated 62 tok/s.
Q4 inference is estimated to need about 16GB VRAM on this page, while NVIDIA RTX 6000 Ada has 48GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.