Qwen Qwen2.5 32B Instruct speed on NVIDIA A100 40GB PCIe and quantization-level VRAM fit.
NVIDIA A100 40GB PCIe meets the minimum VRAM requirement for Q4 inference of Qwen Qwen2.5 32B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA A100 40GB PCIe can run Qwen Qwen2.5 32B Instruct with Q4 quantization. At approximately 80 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 24GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 16GB | 40GB | 79.54 tok/s | ✅ Fits comfortably |
| Q8 | 32GB | 40GB | 55.67 tok/s | ✅ Fits comfortably |
| FP16 | 64GB | 40GB | 30.22 tok/s | ❌ Not recommended |
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NVIDIA A100 40GB PCIe can run Qwen Qwen2.5 32B Instruct at Q4 with an estimated 80 tok/s.
Q4 inference is estimated to need about 16GB VRAM on this page, while NVIDIA A100 40GB PCIe has 40GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.