Can I Run Devstral Small 2 on a Apple M2 (8GB)?
Runs comfortably at Q6_K — minimal quality loss.
3 quantizations fit your 8.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 6.8 GB | 8.3 GB | 5.8 GB | +1.2 GB |
| Q5_K_M | 6.0 GB | 7.5 GB | 5.0 GB | +2.0 GB |
| Q4_K_M | 5.2 GB | 6.7 GB | 4.2 GB | +2.8 GB |
Try it in the cloud first
Don't want to download Devstral Small 2 just to try it? Use a hosted API or rent a GPU by the second.
Affiliate links — we earn a commission at no cost to you.
All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 8.0GB.
FAQ
Can the Apple M2 (8GB) run Devstral Small 2?
Yes. The Apple M2 (8GB)'s 8.0GB of unified memory is enough to run Devstral Small 2 at Q6_K quantization (6.8GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 8.0GB. It uses about 6.8GB of memory and 8.3GB 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.