Simon Willison updates llm-meta-ai 0.2 for Meta AI’s Muse Wonder

What happened

Simon Willison updated his llm-meta-ai plugin to support Meta AI’s newly released Muse Wonder models. He shares pelican drawings across six reasoning levels, from minimal to max, and compares them with Muse 1.3 and Muse 1.2, reporting material drawing improvements between releases. He suggests these may be Meta’s first Fable class models and reports that Artificial Analysis scores Muse Wonder (Max) as equivalent to GPT-6.1 Sol.

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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