Meta Releases Muse Wonder Models for Coding and AI Agents
The company’s first frontier-class models focus on coding, long-running tasks and persistent memory.
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Meta has released Muse Wonder and Muse Wonder Full, its first frontier-class models from Meta Superintelligence Labs, aimed at coding, research and autonomous agent tasks.
The models are larger and more capable than Meta’s Muse Spark systems, which were built for lower-cost and lower-latency use.
Meta said the Wonder models perform competitively with systems including Fable 5.1 and GPT-6 Astra across several benchmarks.
The company is placing particular emphasis on Active Memory, designed to retain relevant information about users over longer periods without requiring the same context to be repeatedly supplied.
“We put a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond,” Meta research scientist Kavya Kopparapu said in the release.
Meta said Muse Wonder outperformed Fable, Opus and Astra on MemoryBench, which tests continual learning and memory construction.
Muse Wonder is available through the Meta Model API and Muse Code at $4 per million input tokens and $20 per million output tokens.
Muse Wonder Full is limited to Muse Code subscribers and is not available through the API.
Both models will also power Meta’s Muse personal AI agent.
“These are true frontier models,” Meta AI chief Alexandr Wang said, adding that the company was focused on personal and professional agent tasks.
