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English(EN) Meta's 816B Muse Spark Open scores 39 on Artificial Analysis, the 180B Qwen3.8-Flash-Next scores 40. Score vs size for 11 open-weight models

Meta的Muse Spark Open和Qwen3.8-Flash-Next基准测试得分公布

作者 PulseAugur 编辑部 · [1 个来源] ·

对开源大语言模型的比较显示了其性能指标与其大小的对应关系。Meta的816B Muse Spark Open模型在Artificial Analysis基准测试中获得39分，而180B Qwen3.8-Flash-Next模型获得40分。分析还指出，MiMo-V2.6-Pro（1T参数）模型获得了最高的46分，其次是DeepSeek V4.1 Flash 1017（552B）和GLM-5.3（753B），得分分别为45分。 AI

影响 提供了开源LLM的性能对比数据，帮助研究人员和开发人员选择模型。

排序理由 该集群讨论了开源大语言模型的基准测试得分，属于研究范畴。[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 →

Meta的Muse Spark Open和Qwen3.8-Flash-Next基准测试得分公布

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该集群讨论了开源大语言模型的基准测试得分，属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

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

    Meta's 816B Muse Spark Open scores 39 on Artificial Analysis, the 180B Qwen3.8-Flash-Next scores 40. Score vs size for 11 open-weight models

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1xcthj8/metas_816b_muse_spark_open_scores_39_on/"> <img alt="Meta's 816B Muse Spark Open scores 39 on Artificial Analysis, the 180B Qwen3.8-Flash-Next scores 40. Score vs size for 11 open-weight models" src="h…

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