Autor: Jakub Rusinowski · Ostatnia aktualizacja: 21 lipca 2026
How much GPU VRAM you need to run Mistral Small 4 Mistral Small 4 119B-A6.5B by Mistral AI locally, a 119B-parameter model. Figures are quantized weights + KV cache + framework overhead from a memory-bandwidth roofline model.
Mistral Small 4 119B-A6.5B needs about 73 GB VRAM at Q4_K_M.
| Quant | Bits/weight | Weights | Total VRAM |
|---|---|---|---|
| Q2_K | 2.63 | 39.1 GB | 39.9 GB |
| Q3_K_M | 3.41 | 50.7 GB | 51.5 GB |
| Q4_K_M | 4.83 | 71.8 GB | 72.6 GB |
| Q5_K_M | 5.67 | 84.3 GB | 85.1 GB |
| Q6_K | 6.56 | 97.6 GB | 98.4 GB |
| Q8_0 | 8.50 | 126.4 GB | 127.2 GB |
| F16 | 16.00 | 238.0 GB | 238.8 GB |
Switch quantization in the interactive calculator, or see the full Mistral Small 4 model page.
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/mistral-small-4-119b)
Estimates only — actual VRAM varies with context length, batch size, runtime and KV-cache settings.