What Models?

Pick the right model for your GPU — in seconds.

What GPU do you need to run Codestral 22B?

22.2B params 32K max context

The smallest GPU memory that runs Codestral 22B well is 18 GB (Q4_K_M, e.g. M3 Pro). 47 of 132 GPUs run it well and 25 more are a tight fit.

MMLU 62

VRAM needed per quantization

QuantizationWeights16K contextFull 32K
Q4_K_M13.3 GB16.7 GB20.1 GB
Q8_023.6 GB27.1 GB30.5 GB

Weights plus fp16 KV cache. Leave ~1 GB headroom for the inference engine.

Cheapest GPUs that can run Codestral 22B

Lowest launch MSRP among GPUs that run its smallest quantization (Q4_K_M) well, with at least 16K context.

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GPUs that can run Codestral 22B

Best quantization that fits on each GPU, with the context and speed it gets. For chips with several memory sizes, the smallest that works is shown.

NVIDIA

AMD

Intel

Apple

  • M1 16 GB Q4_K_M 12K context · ~5 tok/s tight fit
  • M3 Pro 18 GB Q4_K_M 21K context · ~10 tok/s
  • M2 24 GB Q4_K_M 32K context · ~7 tok/s
  • M3 24 GB Q4_K_M 32K context · ~7 tok/s
  • M4 24 GB Q4_K_M 32K context · ~8 tok/s
  • M4 Pro 24 GB Q4_K_M 32K context · ~19 tok/s
  • M5 24 GB Q4_K_M 32K context · ~11 tok/s
  • M5 Pro 24 GB Q4_K_M 32K context · ~21 tok/s
  • M6 24 GB Q4_K_M 32K context · ~12 tok/s
  • M1 Max 32 GB Q8_0 32K context · ~16 tok/s
  • M1 Pro 32 GB Q8_0 32K context · ~8 tok/s
  • M2 Max 32 GB Q8_0 32K context · ~16 tok/s
  • M2 Pro 32 GB Q8_0 32K context · ~8 tok/s
  • M3 Max 36 GB Q8_0 32K context · ~12 tok/s
  • M4 Max 36 GB Q8_0 32K context · ~17 tok/s
  • M5 Max 36 GB Q8_0 32K context · ~19 tok/s
  • M1 Ultra 64 GB Q8_0 32K context · ~32 tok/s
  • M2 Ultra 64 GB Q8_0 32K context · ~32 tok/s
  • M3 Ultra 96 GB Q8_0 32K context · ~33 tok/s
  • M5 Ultra 96 GB Q8_0 32K context · ~49 tok/s
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