Openpipe Qwen3 14B Instruct speed on Apple M3 Pro and quantization-level VRAM fit.
Apple M3 Pro meets the minimum VRAM requirement for Q4 inference of Openpipe Qwen3 14B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
Apple M3 Pro can run Openpipe Qwen3 14B Instruct with Q4 quantization. At approximately 15 tokens/second, you can expect Basic speed - best for non-interactive tasks.
You have 29GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 7GB | 36GB | 15.10 tok/s | ✅ Fits comfortably |
| Q8 | 14GB | 36GB | 10.57 tok/s | ✅ Fits comfortably |
| FP16 | 28GB | 36GB | 5.74 tok/s | ✅ Fits comfortably |
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Apple M3 Pro can run Openpipe Qwen3 14B Instruct at Q4 with an estimated 15 tok/s.
Q4 inference is estimated to need about 7GB VRAM on this page, while Apple M3 Pro has 36GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.