meta Muse Wonder

Muse Wonder by meta excels in the Coding category, where it ranks #232 with a composite score of 40/100. Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with... It is particularly strong in areas highlighted by its top benchmark performance and adoption metrics, making it suitable for both individual developers and enterprise teams looking for a reliable coding solution.

Muse Wonder is priced at $4.00 per million input tokens and $20.00 per million output tokens (USD). Contact the provider for volume discounts and enterprise pricing. Pricing is competitive within the coding category and reflects the model's quality-to-cost ratio.

In the Coding category, Muse Wonder holds rank #232 out of 438 models tracked. Its quality rank is #232 and adoption rank is #232. You can use our comparison tool at /compare to see detailed side-by-side metrics with specific alternatives. Key differentiators include its composite scoring across benchmarks, community sentiment, and real-world adoption rates.

Muse Wonder has been evaluated across 5 different signals. Its strongest areas include Capabilities (100/100), Pricing (80/100), Context Window (96/100). These scores are derived from industry-standard benchmarks, community ratings, and real-world performance metrics. The composite score of 40/100 reflects a weighted combination of all tracked signals.

Muse Wonder is a paid model, though some providers may offer trial credits or limited free tiers for evaluation. Check meta's website for current free tier availability and promotional offers.

Muse Wonder supports a 1,049K token context window (1,048,576 tokens total). That translates to roughly 786,432 words in a single prompt. This is large enough to process entire codebases, research papers, or long conversation histories in one shot.

Muse Wonder can generate up to 944K output tokens (943,718 tokens) per response. That is roughly 707,789 words. This is enough for generating complete code files, detailed reports, or long-form content in a single response.

Muse Wonder supports image understanding (vision), function/tool calling, structured JSON output, extended reasoning/chain-of-thought, web search, streaming responses. Function calling lets you integrate it with external APIs and tools programmatically. Vision support means it can analyze images, screenshots, and diagrams alongside text. These capabilities determine which workflows and integrations the model can handle natively.

Muse Wonder was developed by meta. It was released on October 12, 2026. You can access it through meta's API. Check our provider page for all models from meta and how they compare against each other.

Pick Muse Wonder when you need a budget-friendly option for high-volume, simpler tasks where you prioritize cost over peak performance. If your task is straightforward text completion or classification, a cheaper model might give you 90% of the quality at a fraction of the price. Run a quick benchmark on your actual use case before committing.

You can access Muse Wonder through meta's API using standard HTTP requests or their official SDK. Most providers support OpenAI-compatible endpoints, so switching between models often requires changing just the model name in your API call. Streaming is supported for real-time token-by-token output. For production use, implement proper error handling, rate limiting, and cost monitoring.