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Unsloth releases Dynamic V3.1 GGUF quantizations of Qwen3.8-27B

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Unsloth AI releases Dynamic V3.1 GGUF quantizations of Qwen3.8-27B, which it says gain 5–10% accuracy at the same size over its earlier UD3 quants.

The company says the quantizations lead by 5–10% on average across Terminal Bench, DeepSWE and other benchmarks, and that they run on 12GB RAM. The 3-bit quants were not updated because Unsloth found UD3 performs on par with UD3.1. Unsloth says its quants beat GSQ-RCO and Exllama-v3 on the Pareto frontier for Terminal Bench and DeepSWE, and that the GGUFs are available on Hugging Face. Unsloth also says it is working on a better version for Qwen4. These figures are the company's own claims in its announcements on X.

Written by AI from the articles below · updated Nov 11, 11:07 AM ET

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Latest developmentNov 11, 10:50 AM ET
Unsloth releases Dynamic V3.1 Qwen3.8-27B GGUF quantizations

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The articles in this story. Times are ET.

Nov 11
  1. Daniel HanX
    Unsloth releases Dynamic V3.1 Qwen3.8-27B GGUF quantizations

    AIUnsloth releases new Qwen3.8-27B GGUF quantizations using Dynamic V3.1, which it says gain 5-10% accuracy at the same size over UD3 and other quants. The 3-bit quants were not updated because Unsloth found UD3 performs on par with UD3.1, and it says its quants beat GSQ-RCO and Exllama-v3 on the Pareto frontier for Terminal Bench and DeepSWE. The GGUFs are available on Hugging Face.

    Image from @danielhanchen's post
  2. Unsloth AIOfficial
    Unsloth releases Dynamic V3.1 GGUFs for Qwen3.8-27B

    AIUnsloth AI releases Dynamic V3.1 GGUF quantizations of Qwen3.8-27B, which it says lead by 5–10% on average across Terminal Bench, DeepSWE, and other benchmarks. The company says the models run on 12GB RAM and is working on a better version for Qwen4.

    Image from @UnslothAI's post

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