Meta's Muse Wonder models are built for agents that remember and keep going
Muse Wonder and Muse Wonder Full add Active Memory and Active Focus, two features aimed at long-running personal and professional agent tasks.
Meta introduced Muse Wonder and Muse Wonder Full on October 12, calling them its most capable models to date. Meta pitches them for personal and professional agent work such as insurance claims, lease review and personal finances, as well as coding.
Two features stand out. Active Memory keeps relevant details across conversations and pulls them into the current task. Active Focus is meant to keep an agent working toward a goal: pushing through blockers, trying alternatives, recovering from errors, and asking for confirmation before consequential actions.
Muse Wonder is available through the Meta Model API and Muse Code, Meta's coding product. Muse Wonder Full is available to Muse Code subscribers. According to Aiholics, Meta's announcement did not include benchmark scores or pricing, and OpenRouter's catalogue lists Muse Wonder at $4 per million input tokens and $20 per million output tokens.
Why it matters for builders
Memory across sessions and confirm-before-acting are the two things most agent builders currently hand-roll. If a model handles them natively, your agent code can get simpler. Check the confirmation behavior on your own risky actions before relying on it.
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