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metadata
license: other
license_name: modified-mit
library_name: mlx
base_model: moonshotai/Kimi-K2-Instruct
pipeline_tag: text-generation
tags:
  - mlx

See Kimi-K2 Dynamic MLX in action - https://youtu.be/-zfUvA2CDqE

q3.95bit dynamic quant typically achieves 1.243 perplexity in our testing, slotting closer to q4 perplexity (1.168) than q3 perplexity (1.900).

Quantization Perplexity
q2 41.293
q3 1.900
q3.95 1.243
q4 1.168
q6 1.128
q8 1.128

Usage Notes

  • Runs on a single M3 Ultra 512GB RAM using Inferencer app
  • Requires expanding VRAM limit to at least ~500000 MB
    • For a larger context window, 507000 is used in VRAM limit command below.
    • sudo sysctl iogpu.wired_limit_mb=507000
  • Expect ~20 tokens/s
  • Quantized with a modified version of MLX 0.26
  • For more details see demonstration video or visit Kimi K2.

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.