Description

This repo contains specialized MoE-quants for Mistral-Small-4-119B-2603. The idea being that given the huge size of the FFN tensors compared to the rest of the tensors in the model, it should be possible to achieve a better quality while keeping the overall size of the entire model smaller compared to a similar naive quantization. To that end, the quantization type default is kept in high quality and the FFN UP + FFN GATE tensors are quanted down along with the FFN DOWN tensors.

Notes

I had made a Q4_K_M mix, but it kept returning NaN's for the KLD / PPL testing so I'm looking more into that.

Quant Size Mixture PPL 1-(Mean PPL(Q)/PPL(base)) KLD
Q5_K_M 82.06 GiB (5.92 BPW) Q8_0 / Q5_K / Q5_K / Q6_K 5.773442 ± 0.037218 +0.3924% 0.054105 ± 0.000366
IQ4_XS 53.09 GiB (3.83 BPW) Q8_0 / IQ3_S / IQ3_S / IQ4_XS 5.980665 ± 0.038900 +3.9957% 0.132002 ± 0.000692
IQ3_S 40.89 GiB (2.95 BPW) Q8_0 / IQ2_S / IQ2_S / IQ3_S 6.506233 ± 0.043705 +13.1347% 0.261355 ± 0.001217

kld_graph ppl_graph

Downloads last month
575
GGUF
Model size
119B params
Architecture
mistral4
Hardware compatibility
Log In to add your hardware

3-bit

4-bit

5-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for AesSedai/Mistral-Small-4-119B-2603-GGUF

Quantized
(36)
this model