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English(EN) QUASAR 4-bit QAT checkpoints for Qwen3.5, Gemma 4 and Muse Glimmer: closer to BF16 than Google’s and NVIDIA’s 4-bit releases

QUASAR 发布 Qwen 3.5、Gemma 4、Muse Glimmer 的 4 位量化检查点

作者 PulseAugur 编辑部 · [1 个来源] ·

QUASAR 发布了针对 Qwen 3.5、Gemma 4 和 Muse Glimmer 等多个大型语言模型的新 4 位量化检查点。这些检查点使用感知量化蒸馏进行训练，旨在实现比 Google 和 Nvidia 现有的 4 位版本更接近原始 BF16 模型的性能。基准测试表明，QUASAR 检查点在各种指标上通常优于参考模型，其中一些在性能上可与 BF16 模型相媲美甚至超越。 AI

影响 为在性能较低的硬件上运行大型语言模型提供了改进的性能和效率。

排序理由 发布量化模型检查点并进行基准测试比较。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

QUASAR 发布 Qwen 3.5、Gemma 4、Muse Glimmer 的 4 位量化检查点

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6 / 100
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Tool
发布量化模型检查点并进行基准测试比较。[lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, infra
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High
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Breaking (< 6h)
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报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Mindless_Ad_407 ·

    QUASAR 4-bit QAT checkpoints for Qwen3.5, Gemma 4 and Muse Glimmer: closer to BF16 than Google’s and NVIDIA’s 4-bit releases

    <!-- SC_OFF --><div class="md"><p>Two months ago we released a <a href="https://huggingface.co/QUASAR-QAT/Qwen3.8-27B-QUASAR-NVFP4">fully quantized NVFP4 Qwen3.8-27B</a> trained with QUASAR. We've since trained QUASAR checkpoints for a bunch of other recent models: Qwen3.5-4B, Ge…

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