Ilyagusev Saiga Llama3 8B speed on Apple M2 Ultra and quantization-level VRAM fit.
Apple M2 Ultra meets the minimum VRAM requirement for Q4 inference of Ilyagusev Saiga Llama3 8B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
Apple M2 Ultra can run Ilyagusev Saiga Llama3 8B with Q4 quantization. At approximately 81 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 187GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 5GB | 192GB | 80.51 tok/s | ✅ Fits comfortably |
| Q8 | 9GB | 192GB | 56.36 tok/s | ✅ Fits comfortably |
| FP16 | 17GB | 192GB | 30.60 tok/s | ✅ Fits comfortably |
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Apple M2 Ultra can run Ilyagusev Saiga Llama3 8B at Q4 with an estimated 81 tok/s.
Q4 inference is estimated to need about 5GB VRAM on this page, while Apple M2 Ultra has 192GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.