Developers Get the Weaker Muse Wonder. The Stronger One Stays Inside Muse Code
Meta has released its first models it calls frontier-class, meaning built to compete with the best AI systems available. An outside evaluator rates them competitive, but the widest leads come from tests Meta chose and ran itself.
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Oct 12, 22:00 UTC ·
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Meta released two new AI models on October 12, Muse Wonder and the more capable Muse Wonder Full, which it calls its most capable to date and its first step to the frontier of AI. [2]
An independent evaluator largely backs the claim that they are competitive. It does not back every margin Meta advertises. [5]
What Meta is claiming
"Frontier" is an industry word, not a certification. It means a model competing near the leading edge of what AI can currently do. Nobody awards the title, so a company has to earn it by being measured against rivals' flagships.
Meta's announcement describes the pair as the step from rebuilding its AI foundations to pushing the frontier. [2] The company says it overhauled its AI effort 14 months before this release. [2]
The models are pitched at agent work, meaning tasks where an AI plans and carries out many steps on its own, such as working through an insurance claim or a lease, and at coding. [2] Meta says an Active Memory feature carries useful details across conversations. It says Active Focus keeps the model working on a hard task, trying other approaches and recovering from errors. [2]
The jump from the last model is large in scale. Meta introduced Muse Spark in April 2026 as the first of its Muse series, small and fast, with bigger models still in development. [4] TechCrunch reports that Wonder is larger than Spark and was trained at Meta's Prometheus data center in central Ohio, which came online earlier this year. [1]
Meta's scorecard
On Meta's own Personal Superintelligence Index, Wonder Full scored 59.1. Claude Opus 5.5 scored 55.2 and GPT-6 Astra 54.5. [3] Decrypt reports that Meta has not published the formula behind the index, so outsiders cannot rebuild the number. [3]
The coding result is starker. On Meta's SWE-Marathon test, Wonder Full scored 57.5 against 46.3 for Opus 5.5 and 42.5 for Astra. [3] Decrypt says Meta acknowledged the comparison was not controlled and that Wonder Full ran at maximum effort, a setting that lets a model spend longer working through a problem before it answers. [3]
TechCrunch reports that the tests in Meta's model card show higher scores than Spark and stronger results on complex tasks such as coding. A model card is the document in which a developer publishes a model's details and test results. TechCrunch notes these are Meta's evaluations, not independent replications. [1]
A test that is not controlled can still be honest, but it cannot say how much of an 11-point gap belongs to the model and how much to the way the race was run.
The outside check
Artificial Analysis, an independent evaluator, ran both models through its Intelligence Index, which combines 10 evaluations. At maximum reasoning effort, the same think-longer setting, Wonder Full scored 56 and Wonder 52. Muse Spark 1.3 scored 48. [5] The evaluator says Wonder Full improved on Spark across all 10 tests. [5]
That is a real result. An eight-point gain over the previous model, across every component, is hard to produce by choosing a flattering benchmark.
The same ranking shows where the lead ends. Decrypt reports that Artificial Analysis placed Opus 5.5 at 58, Wonder Full at 56, and GPT-6 Astra and Claude Fable 5.1 at 53 each. [3] Meta's own index put Wonder Full nearly four points ahead of Opus 5.5. Artificial Analysis puts it two points behind.
The two indexes measure different things, so neither is wrong. The gap between them shows how much a result depends on who picked the test.
Which model you can actually use
The version most developers can reach is the weaker one. Meta made Wonder available through its API, the software doorway developers use to build their own apps on a model, and to users of Muse Code, its coding product. Wonder Full is open only to Muse Code subscribers. [2]
Wonder, the version available through Meta's API, scored 52 on the Intelligence Index, a point below GPT-6 Astra and Claude Fable 5.1. [3]
Artificial Analysis says Wonder's API price is $4 per million input tokens and $20 per million output tokens. A token is a small chunk of text, roughly a word fragment, and it is the unit AI companies bill by. Wonder Full has no per-token price because it is sold only through Muse Code. [5]
On coding, the outside numbers are good for Meta. Artificial Analysis says Wonder Full tied Claude Code with Sonnet 5.5 at 68 on its Coding Agents Index, while Wonder scored 63. [5] Those runs were done through Muse Code, so they measure a model inside a product, not the SWE-Marathon comparison Meta published. [5]
What it means for Meta
Muse Wonder suggests Meta can now build models that sit among the leaders, on the one outside test we have. It does not show that Meta has passed them. On that index Wonder Full lands two points behind one rival, and ahead of two others.
The commercial question is whether developers will build on it. Wonder is priced and available for that. Wonder Full, the better model, is tied to a Meta subscription product. Meta says Wonder will soon power its Muse assistant, first for subscribers. [2]
There is also the matter of trust. A model that remembers personal details across conversations is a different proposition from one that answers a question and forgets you. Meta says it trained the models to protect private information, refuse harmful requests and support defensive cybersecurity work. [2] The company has not yet released the evidence. It says a fuller safety report will be available soon. [2]
No independent tests of reliability when the models use tools or handle long multi-step tasks have been reported so far. Meta has not said whether it will release the models' weights, the trained numbers that make up the model and that outsiders would need to run it themselves. Neither a launch date for Wonder in the Muse assistant nor a price for Wonder Full has been given.
The next check is Meta's promised safety report, and whether it comes with enough evaluation detail for outside researchers to rerun the tests themselves.
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- Meta releases its first frontier model, Muse Wonder | TechCrunch TechCrunch
- Introducing Muse Wonder and Muse Wonder Full: Frontier Models for Agents about.fb.com
- Meta's New Muse Wonder Finally Puts Zuckerberg in the Frontier AI Race - Decrypt decrypt.co
- Introducing Muse Spark: Meta's Most Powerful Model Yet about.fb.com
- Muse Wonder and Muse Wonder Full: a material jump in intelligence over previous Meta models | Artificial Analysis artificialanalysis.ai