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  1. Models
  2. Text
  3. Meta

Muse Glimmer 30B

Meta's Muse Glimmer 30B is a dense, open-weight multimodal model distilled from Muse Spark for long-horizon agents and coding workflows. It supports multi-step reasoning, reliable tool use, failure recovery, image understanding, and more than 100 languages.

  • Reasoning
  • Vision
  • Tool Calling
  • Structured Output

Added Aug 11, 2026

Model weights

Pricing

Auto routing · per 1M tokens
Input
$0.35
Output
$1.50
Cache read
$0.04
Compare provider prices

Specifications

Context window
131.1K
Max output
131.1K
Parameters
30B
Avg output (7d)
572 tokens
Longer than 52% of models

Benchmarks

Sourced from Artificial Analysis.

Intelligence Index

6.3

Intelligence Index: 6.3
Better than 7% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

6.8%

Better than 28% of models compared

AutomationBench-AA Tasks Completed

Fully completed workflows without guardrail violations

0.8%

Better than 28% of models compared

AA-Briefcase v1.1

Agentic knowledge work (Elo)

478 Elo

Better than 20% of models compared

GDPval-AA v2.1

Economically valuable tasks (Elo)

792 Elo

Better than 33% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

10.0%

Better than 39% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

83.3%

Better than 96% of models compared

Reasoning

HLE

Humanity's Last Exam

22.0%

Better than 68% of models compared

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

0.5%

Better than 33% of models compared

SciCode

Python programming for scientific computing

44.9%

Better than 35% of models compared

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

83.5%

Better than 73% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

83.3%

Better than 96% of models compared

Last updated Oct 31, 2026

Artificial Analysis

Providers

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Muse Spark Open

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Muse Wonder

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Meta's Muse Wonder is a frontier reasoning model designed for complex personal and professional agentic tasks. It accepts text, images, audio, video, and PDF documents across a one-million-token context window, supports tool calling and structured output, and always reasons before answering.

Muse Spark 1.3

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Muse Spark 1.3 Contributor

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Muse Spark 1.2

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Muse Spark 1.2 Contributor

meta/muse-spark-1.2-contributor

A much cheaper opt-in version of Muse Spark 1.2 with the same multimodal coding and agentic capabilities. Prompts and outputs sent to this Contributor model may be used by Meta for training and to improve its products; use the standard Muse Spark 1.2 model if you do not want your data used for training.