Website
1366Elo
Win rate 62.6%
Muse Wonder
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.
- Input / output price
- $4/$20per 1M tokens
- Context
- 1.0M
- Released
- 2026-10-12
Pricing
Design Arena
Elo scores and win rates across design and agent tasks.
Category performance
1,000-1,500 EloModel Arena
Code Categories
1382Elo
Win rate 62.3%
3D
1445Elo
Win rate 61.9%
UI Component
1378Elo
Win rate 63.3%
Game Development
1403Elo
Win rate 62.2%
Data Visualization
1304Elo
Win rate 55.4%
Agent Arena
Blender3d
1232Elo
Win rate 50.2%
Htmlslides
1133Elo
Win rate 13.9%
Spreadsheet
1279Elo
Win rate 49.7%
Python-pptxslides
1096Elo
Win rate 14.2%
Related Models
Muse Spark 1.3
metaMuse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through conflicting inputs, and request clarification or confirmation when needed, with an emphasis on concise execution.
- Context
- 1.0M
- Max output
- 943.7K
- Released
- 2026-09-02
- Input
- $1.25/M
- Output
- $4.25/M
- Cache read
- $0.15/M
Muse Spark 1.2
metaMuse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, and PDF documents, returns text, and offers a 1M-token context window. The model is built to support multi-agent workflows, whether as either a main agent that plans and delegates or as a subagent executing in parallel. It works across multiple coding harnesses and supports structured output, parallel function calling, and configurable reasoning effort. In Meta’s testing, it performs well on multi-file refactors, extended debugging sessions, whole-repository generation, and tasks that stretch well past a single prompt.
- Context
- 1.0M
- Max output
- 943.7K
- Released
- 2026-08-05
- Input
- $1.25/M
- Output
- $4.25/M
- Cache read
- $0.15/M
Muse Spark 1.1
metaMuse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, and PDF documents and returns text, with a 1M-token context window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates or as a subagent, and generalizes zero-shot to new tools, MCP servers, and custom skills. It supports structured output, parallel function calling, built-in search with citations, and configurable reasoning effort. Meta reports strong performance on real-world coding across large codebases, computer-use workflows, and visual-to-code generation.
- Context
- 1.0M
- Max output
- 943.7K
- Released
- 2026-07-16
- Input
- $1.25/M
- Output
- $4.25/M
- Cache read
- $0.15/M