Meta releases lightweight model Muse Ember, focused on cost-effectiveness for agentic tasks
Meta has released its smallest and most efficient model, Muse Ember, aimed at complex reasoning execution and everyday agentic work; it can take on workflows across applications, call tools in sequence, run tests, and make targeted code fixes. The model supports a 1M-token context window and natively understands text, images, audio, and video. On the Artificial Analysis Intelligence Index, its performance is comparable to Claude Haiku 5.5, with a per-task cost of about one-third of the latter, and it scores higher than GPT-6 Luna across all reasoning settings. Muse Ember is now available on the Meta Model API, priced at $0.10 per million input tokens and $0.50 per million output tokens.
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SelectedAI score 74
Meta has published comparison data on the new model's cost and performance, which can be used to gauge the cost-effectiveness range of lightweight agentic models.
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For agents that perform hundreds of small tasks, efficiency matters at every step. Muse Ember is built to deliver more intelligence for the cost.
On the @ArtificialAnlys Intelligence Index, it achieves performance comparable to Claude Haiku 5.5 at roughly one-third of the cost per task, while scoring higher than GPT-6 Luna across all of Luna's reasoning settings.