Meta's AI research organization, developer of the Llama open models and frontier systems such as Muse.
Meta released Muse Ember, its smallest and most efficient model, positioned against Claude Haiku and GPT-6 Luna for agent workloads such as tool calls, coding subtasks, routing, extraction and long-document parsing. Short-prompt pricing matches rivals at $0.10 per million input and $0.50 output tokens, but long-context tiers rise more steeply, reaching $0.30 input and $1.50 output beyond 200k tokens.
Meta's Muse Ember is now available on OpenRouter, positioned as a sub-task execution model for coding agents. The suggested pattern uses a frontier planner such as Muse Wonder to decompose work, then fans bounded sub-tasks out to Muse Ember for parallel execution. No parameter counts, benchmarks, or pricing details were disclosed.
Meta's Muse Ember (Max) tops the Code Arena WebDev small-model leaderboard at 1608 points, beating Claude Haiku 5.5 and GPT-6 Luna. At identical API pricing, its median cost per task is just $0.03, roughly half of Luna and a quarter of Haiku, placing it on the cost-performance Pareto frontier. Generations averaged about two minutes each, producing 20+ websites and animations in a single pass.