See Mistral-Small-4-119B-2603 MLX in action - demonstration video

Tested on a M3 Ultra 512GB RAM using Inferencer app v1.10.7

  • Text inference ~48.87 tokens/s @ 1000 tokens
  • Vision inference ~ tokens/s (available from v1.11.0)
  • Batched inference ~ total tokens/s across five inferences
  • Memory usage: ~126.8 GiB

q9bit quant typically achieves near lossless accuracy in our coding test

QuantizationPerplexityToken AccuracyMissed Divergence
q3.5168.043.45%72.57%
q4.51.3359391.65%27.61%
q4.81.2812593.75%21.15%
q5.51.2343795.05%17.28%
q6.51.2187596.95%12.03%
q8.51.2109397.55%10.50%
q91.2109397.55%10.50%
Base1.20312100.0%0.000%
Quantized with a modified version of MLX
For more details see demonstration video or visit Mistral-Small-4-119B-2603.

Disclaimer

We are not the creator, originator, or owner of any model listed. Each model is created and provided by third parties. Models may not always be accurate or contextually appropriate. You are responsible for verifying the information before making important decisions. We are not liable for any damages, losses, or issues arising from its use, including data loss or inaccuracies in AI-generated content.

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