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Meta introduces Muse Wonder and Muse Wonder Full for agentic tasks
- Who
- Meta
- What
- introduced the Muse Wonder series, including Muse Wonder and Muse Wonder Full
What happened
Meta introduces Muse Wonder and Muse Wonder Full, describing them as its most capable models yet and frontier models built for personal and professional agentic tasks. Muse Wonder is available today via the Meta Model API and Muse Code. Muse Wonder Full is available today for Muse Code subscribers. Muse Wonder will also soon power experiences in Meta’s personal agent product, Muse, rolling out first to subscribers.
The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》
Reported by 7 sources
The story so far
Meta released Muse Wonder through the Meta Model API and Muse Code and Muse Wonder Full for Muse Code subscribers, while Alexandr Wang said the team was addressing a bug in how both models counted against subscribers’ usage limits. Wang promised resets once the bug was fixed; his subsequent update said issues remained. TechCrunch reports that Wonder’s API pricing is $4.00 per million input tokens and $20.00 per million output tokens. Artificial Analysis reports that Wonder and Wonder Full scored 52 and 56 on its Intelligence Index v4.3 at maximum reasoning effort, compared with 48 for Muse Spark 1.3 at the same setting. Full improved across all ten evaluations, with its largest gains in agentic evaluations. Both models support a one-million-token context window. Meta says its internal benchmarks show performance competitive with GPT-6 Astra, Claude Opus 5.5 and Claude Fable 5.1, while The Decoder reports weaker factual knowledge than leading competitors despite stronger coding and agent results. Statements about access through Meta’s personal agent, Muse, differ: Meta’s announcement says Wonder will power it soon, starting with subscribers, while Baoyu reports that Zuckerberg said subscribers could use it at launch. In his latest comments, Wang acknowledged there was still much to improve in response to a Wonder Full review that praised its writing and orchestration but criticized pricing and usage limits.
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