Redhatai Llama 3.3 70B Instruct FP8 Dynamic speed on Apple M4 Pro and quantization-level VRAM fit.
Apple M4 Pro meets the minimum VRAM requirement for Q4 inference of Redhatai Llama 3.3 70B Instruct FP8 Dynamic. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
Apple M4 Pro can run Redhatai Llama 3.3 70B Instruct FP8 Dynamic with Q4 quantization. At approximately 13 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 | 35GB | 64GB | 12.82 tok/s | ✅ Fits comfortably |
| Q8 | 70GB | 64GB | 8.97 tok/s | ❌ Not recommended |
| FP16 | 140GB | 64GB | 4.87 tok/s | ❌ Not recommended |
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Apple M4 Pro can run Redhatai Llama 3.3 70B Instruct FP8 Dynamic at Q4 with an estimated 13 tok/s.
Q4 inference is estimated to need about 35GB VRAM on this page, while Apple M4 Pro has 64GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.