Meta
Muse Wonder
Meta's models for coding and longer tasks

Key facts
- 12 Oct 2026
- Released
- 1M tokensboth variants
- Context
- $4 / $20input / output per million tokens
- Wonder API
- Muse CodePower or Maximum subscription
- Full access
Meta's Muse Wonder family handles coding and multi-step tasks. Wonder has a preview API; Wonder Full is available through selected Muse Code subscriptions.
Muse Wonder and Muse Wonder Full are AI models from Meta that help write software and carry out tasks with several steps. Meta released the family on 12 October 2026, with tools for coding, planning and computer use.
Both variants have a one-million-token context window, the amount of material a model can work with in a request. Their access differs: Wonder is available through the Meta Model API and Muse Code, while Full requires a Power Usage or Maximum Usage Muse Code subscription.
Choose the access route for the task
Meta’s product page lists these options as of 13 October 2026:
| Model | Access | Context | Published price |
|---|---|---|---|
| Muse Wonder 1.0 | Meta Model API and Muse Code | 1M tokens | API: $4 input, $0.20 cached input, $20 output per million tokens |
| Muse Wonder Full 1.0 | Muse Code Power or Maximum | 1M tokens | Subscription: $50 or $200 per month, with different usage allowances |
The API overview labels Wonder’s API a preview. Use the documented model identifier, muse-wonder-1.0, and check the chosen service’s current availability and limits. A subscription allowance and a token-based API bill measure usage differently.
Longer tasks still need checks
Meta describes the models as able to plan work, use tools and recover from errors during long tasks. It also describes active memory for retaining useful context. These are the company’s descriptions of the models’ intended capabilities.
A useful evaluation starts with a real task, a clear completion check and the permissions the task requires. For coding, check that the resulting software behaves correctly. For computer use, check the action and its result before granting access to more sensitive systems. The AI agents directory covers tools that put these capabilities to work.
Compare a benchmark with its test conditions
Meta publishes results across coding, computer use and professional tasks on its model page. Scores depend on the model version, reasoning setting and surrounding tools. Compare results from the same test and setup before drawing a conclusion about which model suits a job.
The LLM directory tracks other releases. Muse Spark remains a separate Meta family with its own versions and prices.
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- OpenAIGPT-6 Sol and Lunathe mid-price and budget GPT-6 models, released 22 September 2026
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