Codestral 22B — VRAM Requirements
Written by Jakub Rusinowski · Last updated May 29, 2024
How much GPU VRAM you need to run Codestral Codestral 22B by Mistral AI locally, a 22.2B-parameter model. Figures are quantized weights + KV cache + framework overhead, computed from the model's parameter count and published architecture — not a throughput model. See /en/methodology.
Codestral 22B needs about 16 GB VRAM at Q4_K_M.
VRAM by Quantization
| Quant | Bits/weight | Weights | Total VRAM |
|---|---|---|---|
| Q2_K | 2.63 | 7.3 GB | 10.0 GB |
| Q3_K_M | 3.41 | 9.5 GB | 12.1 GB |
| Q4_K_M | 4.83 | 13.4 GB | 16.1 GB |
| Q5_K_M | 5.67 | 15.7 GB | 18.4 GB |
| Q6_K | 6.56 | 18.2 GB | 20.9 GB |
| Q8_0 | 8.50 | 23.6 GB | 26.3 GB |
| F16 | 16.00 | 44.4 GB | 47.1 GB |
Switch quantization in the interactive calculator, or see the full Codestral model page.
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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/codestral-22b?utm_source=badge&utm_medium=referral&utm_campaign=readme_badge&utm_content=codestral-22b)Estimates only — actual VRAM varies with context length, batch size, runtime and KV-cache settings.