Meta Unveils Muse Ember Small Model at $0.03 Per Task
Meta has introduced Muse Ember, its smallest and most efficient model to date, targeting complex reasoning execution and everyday agent workflows with cross-app operation, sequential tool calling, test running and targeted code fixes, plus a 1M-token context and native multimodal understanding. It tops the Code Arena WebDev small-model ranking at 1608 points, beating Claude Haiku 5.5 and GPT-6 Luna, while sitting on the Pareto frontier at a median cost of just $0.03 per task.
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Arena.ai (@arena) · 2026-11-09 18
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 0.50 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.
↳ 引用 @AIatMeta (AI at Meta): 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.
