Deepseek AI Deepseek Coder 33B Instruct speed on Apple M2 Pro and quantization-level VRAM fit.
Apple M2 Pro meets the minimum VRAM requirement for Q4 inference of Deepseek AI Deepseek Coder 33B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
Apple M2 Pro can run Deepseek AI Deepseek Coder 33B Instruct with Q4 quantization. At approximately 12 tokens/second, you can expect Basic speed - best for non-interactive tasks.
You have 15GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 17GB | 32GB | 11.74 tok/s | ✅ Fits comfortably |
| Q8 | 34GB | 32GB | 8.22 tok/s | ❌ Not recommended |
| FP16 | 67GB | 32GB | 4.46 tok/s | ❌ Not recommended |
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Apple M2 Pro can run Deepseek AI Deepseek Coder 33B Instruct at Q4 with an estimated 12 tok/s.
Q4 inference is estimated to need about 17GB VRAM on this page, while Apple M2 Pro has 32GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.