Meta launches Muse Ember small multimodal model at $0.10 per million input tokens

Meta introduced Muse Ember on 9 November 2026 as the compact, low-latency member of its proprietary Muse model family. Accepting native text, image, audio and video inputs across a 1M-token context window, the model targets multi-step coding agents, visual perception pipelines and voice interfaces. Developers can call Muse Ember through the Meta Model API, Muse Code and Google Cloud Vertex AI, while consumer rollouts extend the model to Meta AI on Apple Watch and WearOS smartwatches.

Efficiency and evaluation discrepancies

On the Meta Model API, Muse Ember costs $0.10 per million uncached input tokens, $0.004 per million cached input tokens, and $0.50 per million output tokens. According to Meta and Artificial Analysis, Muse Ember matches Anthropic’s Claude Haiku 5.5 at 36 on the Artificial Analysis Intelligence Index while finishing the benchmark suite at an average cost of roughly $0.14 ($0.136) per task against $0.411 for Haiku 5.5. Meta’s benchmark charts on the research blog are rendered interactively in HTML rather than as downloadable images. One figure differs across sources: Meta’s research table lists 37.8% on AutomationBench-AA, whereas Artificial Analysis’s summary post reports 68.1% on the same benchmark.

Key numbers

• $0.10 input, $0.004 cached input, and $0.50 output per million tokens across a 1M-token window
• 1608 Arena Elo on Code Arena WebDev, ranking first among small models
• 61.6% on Agents’ Last Exam and 40.9% on Terminal-Bench 4.0
• 80.6% on PerceptionBench with tool use and 46 on Coding Agent Index-AA