Intelligence index
Outperforms 50% of compared models
Muse Glimmer 30B
Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon agentic and coding workflows, with multi-step reasoning, reliable tool use, failure recovery, image understanding, and multilingual support across more than 100 languages.
- Input / output price
- $0.3/$1.2per 1M tokens
- Context
- 131K
- Released
- 2026-08-09
Pricing
Artificial Analysis
Explore rankingsCoding index
Outperforms 50% of compared models
Agentic index
Outperforms 40% of compared models
Design Arena
Elo scores and win rates across design and agent tasks.
Category performance
1,000-1,500 EloModel Arena
Website
1161Elo
Win rate 34.7%
Code Categories
1149Elo
Win rate 33.3%
Game Development
1117Elo
Win rate 30.3%
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