Meta Releases Muse Ember, a 1M-Context Model for High-Volume Agent Work
Meta Releases Muse Ember, a 1M-Context Model for High-Volume Agent Work
Meta Superintelligence Labs released Muse Ember, a hosted multimodal reasoning model with a 1M-token context window and up to 512K output tokens, aimed at high-volume agent subtasks such as tool calls, routing, extraction and long document parsing. Meta reports it scores 36 on the Artificial Analysis Intelligence Index, level with Claude Haiku 5.5 at max effort, at about $0.14 per index task versus $0.411 for Haiku, though it trails Haiku on FrontierCode 2.0-AA (27.2 versus 34.9). Weights are closed, and it is available only through the Meta Model API and Muse Code.
Useful for teams weighing a cheaper, long-context hosted model for agent workloads against its closed weights and weaker real-repo coding results.
Source: MarkTechPost · marktechpost.com