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  1. Artificial Analysis Articles72

    Meta's Muse Ember is the cheapest model scoring 36 on the Intelligence Index

    Meta's Muse Ember scores 36 on the Artificial Analysis Intelligence Index, matching Claude Haiku 5.5 (max) at $0.14 per task versus $0.41, making it the cheapest model scoring 36 or higher. It stands out on AutomationBench-AA at 68.1% and scores 46 on the Coding Agent Index in Muse Code, but its AA-Omniscience accuracy of 21.1% is the lowest among similarly intelligent models, largely because it declines to answer 64% of questions, keeping its hallucination rate at 17.4%. Pricing is $0.10 input / $0.004 cached input / $0.50 output per 1M tokens, available via Meta's first-party API and Muse Code.

    Why it matters: The piece offers a detailed cost-versus-capability breakdown that helps readers judge whether a cheap efficient-tier model fits agentic and coding workloads.

  2. MarkTechPost77

    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.

    Why it matters: Useful for teams weighing a cheaper, long-context hosted model for agent workloads against its closed weights and weaker real-repo coding results.

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