Can I Run Devstral 2 on a Apple M3 Max (128GB)?
Runs at full precision (f32). Zero quality loss.
14 quantizations fit your 128GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| f32BEST | 97.0 GB | 98.5 GB | 1.8 GB | +31.0 GB |
| fp16 | 49.0 GB | 50.5 GB | 0.9 GB | +79.0 GB |
| Q8_0 | 26.5 GB | 28.0 GB | 25.1 GB | +101.5 GB |
| Q6_K | 20.8 GB | 22.3 GB | 19.4 GB | +107.2 GB |
| Q5_K_M | 18.0 GB | 19.5 GB | 16.8 GB | +110.0 GB |
| Q5_K_S | 17.6 GB | 19.1 GB | 16.3 GB | +110.4 GB |
| Q4_1 | 16.0 GB | 17.5 GB | 14.9 GB | +112.0 GB |
| Q4_K_M | 15.6 GB | 17.1 GB | 14.3 GB | +112.5 GB |
| Q4_K_S | 14.7 GB | 16.2 GB | 13.6 GB | +113.3 GB |
| Q4_0 | 14.5 GB | 16.0 GB | 13.5 GB | +113.5 GB |
| Q3_K_L | 11.7 GB | 13.2 GB | 12.4 GB | +116.3 GB |
| Q3_K_M | 11.1 GB | 12.6 GB | 11.5 GB | +117.0 GB |
| Q3_K_S | 10.2 GB | 11.7 GB | 10.4 GB | +117.8 GB |
| Q2_K | 8.9 GB | 10.4 GB | 8.9 GB | +119.1 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 128GB.
FAQ
Can the Apple M3 Max (128GB) run Devstral 2?
Yes. The Apple M3 Max (128GB)'s 128GB of unified memory is enough to run Devstral 2 at f32 quantization (97.0GB required).
What's the best quantization to use?
f32 is the highest-precision quantization that fits in your 128GB. It uses about 97.0GB of memory and 98.5GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.