Meta releases Muse Ember for low-cost agent execution
Meta Superintelligence Lab released Muse Ember, a lightweight AI model designed for reasoning and recurring agent tasks such as tool calls, coding subtasks, routing, extraction, and long-document parsing. Meta priced it at $0.10 per million input tokens and said it can pair with Muse Wonder in an agentic harness while handling text, images, and audio inputs. Meta used Artificial Analysis’s composite benchmark score to claim that Ember was cheaper and more capable than Anthropic’s Haiku and OpenAI’s Luna, and cost-competitive with DeepSeek V4.1 Flash and GLM 5.3 Flash. These comparative claims were not independently confirmed in the supplied report.
Muse Ember’s low stated input-token price targets high-volume agent execution, while its proposed pairing with Muse Wonder reflects Meta’s strategy of dividing work between a larger planning model and a lighter model for repetitive tasks.
Today, we're introducing Muse Ember, our smallest and most efficient model designed for complex reasoning execution and the work agents repeat all day: tool calls, coding subtasks, routing, extraction, and long document parsing.
Muse Ember delivers more intelligence per dollar than Claude Haiku 5.5 or GPT-6 Luna at any reasoning setting: it matches Haiku's best score at about a third of the cost and beats every Luna setting. It also sits on the efficiency frontier of the full Artificial Analysis leaderboard: no model scores higher for less per task.
Intelligence vs. Cost Per Task
Artificial Analysis Intelligence Index against cost per task at each reasoning effort, from the raw Artificial Analysis results. Muse Ember costs are estimates at proposed pricing.
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- Muse Ember
- Claude Haiku 5.5
- GPT-6 Luna
#Meta#Muse Ember#Muse Wonder#Artificial Analysis#Anthropic Haiku#OpenAI Luna#DeepSeek V4.1 Flash#GLM 5.3 Flash