Devstral-2 123B — VRAM Requirements
作者： Jakub Rusinowski · 最后更新： 2026年7月21日
How much GPU VRAM you need to run Devstral-2 Devstral-2 123B by Mistral AI locally, a 123B-parameter model. Figures are quantized weights + KV cache + framework overhead from a memory-bandwidth roofline model.
Devstral-2 123B needs about 75 GB VRAM at Q4_K_M.
VRAM by Quantization
| Quant | Bits/weight | Weights | Total VRAM |
|---|---|---|---|
| Q2_K | 2.63 | 40.4 GB | 41.2 GB |
| Q3_K_M | 3.41 | 52.4 GB | 53.2 GB |
| Q4_K_M | 4.83 | 74.3 GB | 75.1 GB |
| Q5_K_M | 5.67 | 87.2 GB | 88.0 GB |
| Q6_K | 6.56 | 100.9 GB | 101.7 GB |
| Q8_0 | 8.50 | 130.7 GB | 131.5 GB |
| F16 | 16.00 | 246.0 GB | 246.8 GB |
Switch quantization in the interactive calculator, or see the full Devstral-2 model page.
Add this badge to your model card
Model creators: paste this into your Hugging Face model card README to link readers straight to this VRAM breakdown.
[](https://llmconfigurator.com/en/vram-calculator/devstral-2-123b)Estimates only — actual VRAM varies with context length, batch size, runtime and KV-cache settings.