Meta Superintelligence Lab on Monday released Muse Ember, which it called its smallest and most efficient model yet, the company said. TechCrunch reported the launch, saying Ember is meant for the work agents repeat all day: tool calls, coding subtasks, routing, extraction and long-document parsing.
Why it matters: Meta said Ember is available on the Meta Model API and Muse Code as muse-ember-1.0, at $0.10 per million input tokens, $0.004 per million cached input tokens and $0.50 per million output tokens, with a 1-million-token context window and up to 512,000 output tokens. TechCrunch said Meta is positioning the model as cheaper than rivals such as Anthropic’s Haiku and OpenAI’s Luna on an Artificial Analysis composite, and quoted Meta’s line that “Muse Wonder plans, Muse Ember handles the volume.”
Meta said Ember was the first model trained using Muse Wonder Full, and that it rounds out a portfolio in which Wonder is for the hardest problems, Spark is for coding and agentic workflows, and Ember is for repeatable tasks at scale, at about $0.14 per Artificial Analysis task. TechCrunch said Ember is the fourth model under the Muse brand, after Spark in April, open-source Glimmer in August and Wonder in October, a lineup distinct from the separate Muse consumer agent that recently arrived on Apple Watch and Wear OS.
Meta said Ember can handle text, images and audio, so agents can read screenshots, charts and scanned documents or work from voice memos and meeting recordings without a separate model, and that Ember, Spark and Wonder are now available on Google Cloud and Oracle Cloud.