Muse Wonder at a glance
Meta's most capable models so far target agentic work in law, finance, health, and coding, with Muse Wonder on the Meta Model API and Muse Wonder Full for Muse Code subscribers.
Current standing
As of
- Rank
- #8of 43 models
Muse Wonder Full (Max) · 50.1 on the Artificial Analysis Intelligence Index v5.0.1 (opens in a new tab)
- Recorded at publication
- 44 (v5.0.1)
as of
- Current leader
- Gemini 4 Carbon (Google) · 60
Computed from our daily snapshot; it changes as new models are measured. Meta launches Muse Wonder and Muse Wonder Full, frontier models for agents
What changed with Muse Wonder
On October 12, 2026, Meta introduced Muse Wonder and Muse Wonder Full, built on Muse Spark and described as its most capable models to date. They target personal and professional agent tasks such as handling an insurance claim, reading a lease, or building an app.
Meta highlights Active Memory, which carries relevant details across conversations, and Active Focus, which keeps working through errors and checks in before important actions. Muse Wonder is available to developers through the Meta Model API and Muse Code; Muse Wonder Full is available to Muse Code subscribers. Meta gave no benchmark figures and said a safety report would follow.
Muse Wonder benchmarks and pricing
Values are copied from the linked source on the date shown. They are not IA Compa measurements.
- Artificial Analysis Intelligence Indexas of · Source for Artificial Analysis Intelligence Index: artificialanalysis.ai (opens in a new tab)
- 44 (v5.0.1)
- Output speedas of · Source for Output speed: artificialanalysis.ai (opens in a new tab)
- 123 tokens/s
- Input price per 1M tokensas of · Source for Input price per 1M tokens: artificialanalysis.ai (opens in a new tab)
- $4.00
- Output price per 1M tokensas of · Source for Output price per 1M tokens: artificialanalysis.ai (opens in a new tab)
- $20.00
- Context windowas of · Source for Context window: artificialanalysis.ai (opens in a new tab)
- 1M tokens
How it compares
Other models in the same category that we have covered, using each model's latest recorded value. (Models)
Muse Wonder reasoning effort
Artificial Analysis tests this model at several reasoning-effort settings. Higher effort usually scores higher but costs more and answers more slowly.
Muse Wonder by effort level
Higher effort lets the model think longer. Here is what each setting scores, how fast it writes, and what it costs on Artificial Analysis.
| Effort | Intelligence Index | Output speed (tokens per second) | Cost to run the index | Blended price (3:1) (per 1M tokens) | Price in / out (per 1M tokens) | First token |
|---|---|---|---|---|---|---|
| Max (Muse Wonder (max)) · Best: highest effort with a score, used in the leaderboard | 44 | 123 | $5,414 | $8 | $4 / $20 | 22 s |
| High (Muse Wonder (high)) | 41 | 125 | $3,520 | $8 | $4 / $20 | 9.8 s |
Benchmarked by AA: max · high of 7 available
Where to compare Muse Wonder
Independent leaderboards and official resources for comparing this model yourself. Rankings change often; each site shows its own current data.
Leaderboards
General leaderboards
Official resources
Why Muse Wonder matters for businesses
Artificial Analysis lists Muse Wonder at 44 on its Intelligence Index v5.0.1, about 123 output tokens per second, and $4/$20 per 1M input/output tokens. This is Meta's first broadly available developer API in the Muse line, which gives agencies another frontier option to evaluate.
Sources for this story
- Introducing Muse Wonder and Muse Wonder Full (opens in a new tab)Official
Meta Newsroom · about.fb.com
- Muse Wonder model analysis (opens in a new tab)Benchmark
Artificial Analysis · artificialanalysis.ai
Last verified: . IA Compa summarizes public announcements for business readers. We are not affiliated with the companies mentioned. Always confirm details, pricing, and availability with the official source.
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