Arena 评测显示 Meta Muse Ember (Max) 以 1608 分登顶 Code Arena WebDev 小模型
Arena 宣布 Meta 的 Muse Ember (Max) 在 Code Arena WebDev 中以 1608 分成为表现最好的小模型，超过 Claude Haiku 5.5 (High) 的 1595 分和 GPT-6 Luna (Max) 的 1578 分。
Arena.ai· @arena · X·2026-11-10 02:20· 29 分钟前AI 评分65
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Arena 宣布 Meta 的 Muse Ember (Max) 以 1608 分成为 Code Arena WebDev 中表现最好的小模型，超过 Claude Haiku 5.5 (High) 的 1595 分和 GPT-6 Luna (Max) 的 1578 分。
正文 · 原文
Exciting news: @AIatMeta's Muse Ember (Max) is the highest-performing small model in the Code Arena: WebDev with 1608 pts, outperforming two leading small models from Anthropic and OpenAI:
- Claude Haiku 5.5 (High): #35, 1595 pts
- GPT-6 Luna (Max): #42, 1578 pts
At a 1608 score at a median cost of $0.03 per task, this puts Ember on the Pareto frontier. Neither Haiku 5.5 nor Luna makes it. Despite all three models having the same API pricing of $0.10/$0.50 per million input/output tokens, Ember's median cost per task is 2× lower than Luna ($0.06) and 3.7× lower than Haiku ($0.11).
In our own testing, Ember demonstrated impressive speed and efficiency, completing 25 complex generations in 2 mins per task, at a total cost of just $1.
Huge congrats to @alexandr_wang and the @AIatMeta team on this impressive release! A major step forward for small models that deliver strong real-world coding capabilities at a fraction of the cost.
在 X 查看被引用的帖子Today we're introducing Muse Ember, our smallest and most efficient model, built for complex reasoning execution and everyday agent work.
Muse Ember can carry workflows across apps, call tools in sequence, run tests and make targeted code fixes. With a 1M-token context window and native understanding of text, images, audio and video, it can also work across large document sets and varied inputs.
来源：Arena.ai · x.com
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