By Paul Derrington, Jr.
CEO | Chief Engineer | Research Engineer | Editor, D-CSIL
2 min read
Key Takeaways
Meta launched Muse Ember on November 9, its smallest and most efficient Muse model, built for the repetitive work agents do all day. It costs $0.10 per million input tokens and $0.50 per million output tokens, and Meta says it matches Claude Haiku 5.5's best benchmark score at about a third of the cost per task.
What happened
Meta introduced Muse Ember on November 9, 2026: its smallest and most efficient Muse model, built for complex reasoning execution and the work agents repeat all day — tool calls, coding subtasks, routing, extraction, and long document parsing. It is available today on the Meta Model API and in Muse Code as muse-ember-1.0, and Meta says it is also live on Google Cloud and Oracle Cloud.
Specs: a 1M-token context window with up to 512K output tokens, native understanding of text, images, audio and video, and support for the Responses API. It is the first model Meta trained using Muse Wonder Full, which Meta calls its most advanced model. Meta says: "Muse Wonder plans, Muse Ember handles the volume."
Price and benchmarks
Muse Ember costs $0.10 per million input tokens, $0.004 per million cached input tokens, and $0.50 per million output tokens. Those headline rates cover requests up to 200,000 input tokens; above that, both rates triple, per Meta's announcement. On the Artificial Analysis Intelligence Index, Ember scores 36 — tied with Claude Haiku 5.5 at 36 and ahead of GPT-6 Luna at 28 — at about $0.14 per index task, against $2.39 for Muse Spark 1.3.
Meta's benchmark table, which mixes Artificial Analysis results from November 9 with Meta internal evaluations, is not a clean sweep: Ember leads on AutomationBench-AA (37.8 against Haiku's 13.9 and Luna's 20.2), Agents' Last Exam (61.6 against 57.0 and 57.1), Terminal-Bench 4.0 (40.9 against 39.2 and 16.4) and the Coding Agent Index (46 against 37 and 31). Haiku wins one: FrontierCode 2.0, 34.9 against Ember's 27.2. Every figure here is Meta's or Artificial Analysis's own — no independent replication has been published. Box, an early partner, says Ember scored contracts against negotiation playbooks clause by clause on its Complex Work Eval and landed on the right overall risk rating; Yashodha Bhavnani, Box's VP of AI Products, calls it "a fast, efficient foundation for agents doing real work on enterprise content."
What happens next
Meta describes the lineup this way: Wonder plans, Spark handles coding and agentic workflows, Ember takes the repeatable work at scale. Meta says it has even more efficient models in training. On safety, Meta says Ember was evaluated under its Superintelligence Scaling Framework, including chemical and biological, cybersecurity, and loss-of-control risks, and stayed below the framework's high-risk thresholds, with the same core safety training as the larger models.
The context is the same day's other launch: Anthropic's Claude Fable 5.2 shipped November 9 at $8 per million input tokens and $40 per million output — 80 times Ember's output price.