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Jun Kim
@jundotkim
Open-Source ML Engineer at 🤗 Hugging Face | Creator of oMLX | I build the tools I wish existed for my Mac, then open-source them. junkim.dot
@gmail
.com
Joined February 2026
198
Following
4.7K
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Jun Kim
@jundotkim
2026.10.12 08:10
All my oQe models have been updated with Improved oQe Quantization, available from oMLX 0.7.1. Compared with the previous oQe builds, KL divergence is 11.6–18.1% lower on code and 10.2–13.8% lower on prose, so please give them a try. The full model list is below. KL divergence from the original BF16 model (mean, lower is better) - Qwen3.8-27B oQ4e: code 0.0143 → 0.0117 (-18.1%), prose 0.0696 → 0.0600 (-13.8%) - Qwen3.8-Flash-Next oQ4e: code 0.0877 → 0.0776 (-11.6%), prose 0.1909 → 0.1713 (-10.2%) What's new - Below oQ4, the Engram and N-gram tables stay at 4 bits and are left out of the bit budget. oMLX can serve these tables from SSD instead of memory, so the full bit budget goes to the rest of the model. - Model cards now show the bit distribution and storage breakdown. If you downloaded an earlier oQe build, please re-download it. Improved oQe models (69) - Qwen3.8-Flash-Next: 2.5 · 2.7 · 3 · 3.5 · 4 · 6 · 8 bits - Qwen3.8-Flash-Next FP16: 2.5 · 3 · 3.5 · 4 bits - Qwen3.8-27B: 2.5 · 3 · 3.5 · 4 · 6 · 8 bits - Qwen3.6-35B-A3B: 2.5 · 3 · 3.5 · 4 · 6 · 8 bits - GLM-5.3-Flash: 2 · 2.5 · 3 · 3.5 · 4 · 5 · 6 bits - DeepSeek-V4.1-Flash: 2 · 2.5 · 3 · 4 bits - DeepSeek-V4-Flash-0731: 2.5 · 2.7 · 3 · 3.5 · 4 bits - gemma-4-31B-it: 2.5 · 3 · 3.5 · 4 · 6 · 8 bits - gemma-4-26B-A4B-it: 2.5 · 3 · 3.5 · 4 · 6 · 8 bits - gemma-4-12B-it: 2.5 · 3 · 3.5 · 4 · 6 · 8 bits - clef: 2.5 · 3 · 3.5 · 4 · 6 · 8 bits - clef-flash: 2.5 · 3 · 3.5 · 4 · 6 · 8 bits
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