Updates

  • 5/19/2026: I've uploaded new quants that include the MTP Tensors (@ Q8_0).
  • 3/10/2026: I've uploaded new quants using the new fused Up + Gate conversion, this offers up to a +10% boost in prompt processing speed from my testing.

Description

This repo contains specialized MoE-quants for Qwen3.5-397B-A17B. 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.

Quant Size Mixture PPL 1-(Mean PPL(Q)/PPL(base)) KLD
Q8_0 399.08 GiB (8.51 BPW) Q8_0 3.486040 ± 0.018831 +0.0501% 0.003298 ± 0.000034
Q5_K_M 280.05 GiB (5.97 BPW) Q8_0 / Q5_K / Q5_K / Q6_K 3.488222 ± 0.018848 +0.1127% 0.004782 ± 0.000042
Q4_K_M 234.11 GiB (4.99 BPW) Q8_0 / Q4_K / Q4_K / Q5_K 3.496714 ± 0.018906 +0.3565% 0.008720 ± 0.000078
IQ4_XS 183.48 GiB (3.91 BPW) Q8_0 / IQ3_S / IQ3_S / IQ4_XS 3.542040 ± 0.019138 +1.6573% 0.022898 ± 0.000190
IQ3_S 142.87 GiB (3.05 BPW) Q6_K / IQ2_S / IQ2_S / IQ3_S 3.671774 ± 0.020020 +5.3807% 0.064287 ± 0.000503
IQ2_S 129.74 GiB (2.77 BPW) Q6_K / IQ2_XS / IQ2_XS / IQ3_XXS 3.778894 ± 0.020751 +8.4551% 0.093763 ± 0.000714
IQ2_XXS 120.47 GiB (2.57 BPW) Q4_K / IQ2_XXS / IQ2_XXS / IQ3_XXS 3.878830 ± 0.021458 +11.3233% 0.126053 ± 0.000896

kld_graph ppl_graph

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