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Meta: Muse Wonder

meta/muse-wonder

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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 a 1M-token context window.

The model handles long-horizon work: it plans, delegates to sub-agents, calls tools in parallel, and recovers from errors, so multi-step tasks run to completion without step-by-step direction. It can also operate browsers and desktop and mobile applications, and works across many files in existing repositories to make and verify changes. Muse Wonder carries important context across conversations and retrieves the details relevant to the task at hand. And it's trained for Active Focus, so it works toward your goal even when a task gets challenging.

In Meta's testing, it performs well on complex engineering tasks, extended agentic sessions, and multi-file refactors to tackle developers' most demanding work.

Modalities
In / Out Price
$4 / $20per 1M
Context
1.0M
Released
Oct 12, 2026
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ProvidersPricingPerformanceUptimeBenchmarksAppsActivityFAQExplore

Providers

This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Meta: Muse Wonder (Design Arena and Vals AI)
SourceBenchmarkScore
Design ArenaMuse Wonder (max) Agents Arena Blender3d Elo1147
Design ArenaMuse Wonder (max) Agents Arena Python-Pptxslides Elo1111
Design ArenaMuse Wonder (max) Agents Arena Spreadsheet Elo1259
Design ArenaMuse Wonder (max) Models Arena 3D Elo1428
Design ArenaMuse Wonder (max) Models Arena Code Categories Elo1372
Design ArenaMuse Wonder (max) Models Arena Data Visualization Elo1311
Design ArenaMuse Wonder (max) Models Arena Game Development Elo1379
Design ArenaMuse Wonder (max) Models Arena UI Component Elo1380
Design ArenaMuse Wonder (max) Models Arena Website Elo1363
Vals AIWonder Code Migration v1.172.4%
Vals AIWonder CyberBench v1.180.4%
Vals AIWonder EMB v1.172.5%
Vals AIWonder Finance Agent v2.165.5%
Vals AIWonder Vals Finance Index61.2%
Vals AIWonder HLAB-Vals-1.123.8%
Vals AIWonder IOI66.9%
Vals AIWonder Legal Research Bench50.5%
Vals AIWonder ProofBench v1.184.0%
Vals AIWonder Vals Science Index39.1%
Vals AIWonder SWE-bench Multimodal45.6%
Vals AIWonder Tax Agent Bench36.3%
Vals AIWonder Terminal-Bench 4.049.5%
Vals AIWonder Vals Index64.9%
Vals AIWonder Vibe Code Bench 1-10026.6%
Vals AIWonder Vibe Code Bench v1.183.1%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Not currently available through EU in-region routing. In-region routing docs

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Frequently asked questions

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 a 1M-token context window.

Muse Wonder costs $4.00/M input tokens and $20.00/M output tokens, with separate rates for Cache Read at $0.20/M tokens and Web Search at $2.50/1K calls.

Muse Wonder has a 1,048,576 token context window.

Yes. Muse Wonder accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

Muse Wonder accepts text, images, video, files such as PDFs, and audio as input and returns text.

Muse Spark Open, Muse Spark 1.3 Contributor, Muse Spark 1.3 and 4 more are other text models from Meta.

Muse Wonder was released on October 12, 2026.