Tasks and inputs
Muse Wonder Full is listed for Image-text-to-text, Text generation, Coding & Code Generation. It accepts text, image, video, audio and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 13, 2026
Muse Wonder Full is Meta’s higher-capability Wonder variant for sustained coding and agent work, available through eligible Muse Code subscriptions.
Pricing conditions: Muse Wonder Full is included in eligible Muse Code Power Usage and Maximum Usage subscriptions. It is not served by Meta Model API and has no published per-token API price. muse-wonder-1.0 and its max effort setting do not select Full.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Muse Wonder Full arrived alongside Muse Wonder on 12 October 2026. It is the higher-capability member of the series, intended for difficult professional agent tasks and sustained software engineering. Treat the two variants as distinct choices when reviewing results: a benchmark attributed to Full does not describe an ordinary Wonder API request.
Full is offered through the Power Usage and Maximum Usage subscriptions in Muse Code. It is absent from the pay-as-you-go Meta Model API. The product lists muse-wonder-full-1.0, but that product identifier is not a public API model ID. Raising reasoning effort to max on muse-wonder-1.0 continues to use the ordinary Wonder model.
The series records a 1,048,576-token context window. A separate public maximum output allowance for Full has not been established, so this profile leaves that field empty. Subscription allowances and the mode selected in Muse Code determine usable capacity. An API token rate for ordinary Wonder cannot be used to estimate a Full subscription’s marginal token bill.
Evaluate Full in the product that actually provides it. Use an engineering task that includes exploration, implementation and verification, and record both the subscription settings and the model shown by Muse Code. Compare completed deliverables and required corrections. When evaluating against an API model, state that the product harness and tool access may differ.
Record the exact model identifier, deployment route and request settings with each result. Count complete runs, including rejected outputs, retries and tool calls. When the workflow creates files or code, open the files or execute the existing checks before accepting the result. A plausible first response can hide an incomplete final deliverable.
The specifications describe supported interfaces and request capacity. They do not establish a measured quality ranking or a latency guarantee for your account. SyncDev has not independently benchmarked this model. Choose a deployment after testing the languages, input formats and operating conditions that matter to your users.
Explore meta models, browse model tasks, or compare two models with the same acceptance criteria.
Compare the model on the work you need to complete.
Muse Wonder Full is listed for Image-text-to-text, Text generation, Coding & Code Generation. It accepts text, image, video, audio and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 1.05M context. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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