Muse Glimmer

An open model built for always-on local agents. 30B parameters, licensed under Apache 2.0 and runs on a single GPU — tuned for tool use, long tasks, and failure recovery.

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Documentation

Meet Muse Glimmer

Always-on agents

Built for agents that don't stop with reliable tool-calling, persistent state across restarts, and self-managed memory across hours-long sessions.

Optimized for local deployments

It's small enough to run on a single consumer GPU or Mac, enabling use cases that range from local agents to local coding.

Benchmarks

Muse Glimmer is trained to deliver competitive agentic and coding performance, with multimodal perception built in.

Benchmark

Muse Glimmer-30BHigh reasoning

Gemma4-31BThinking mode

Qwen3.6-27BThinking mode

General agentic

MCP Atlas

75.5

54.2

62.5

DeepSearch QA

74.6

61.7

71.1

τ³-Banking

23.5

15.1

16.7

WildClawBench

47.6

37.6

43.2

GDPval-AA

953

811

1141

GAIA2

43.3

36.4

40.0

SkillsBenchWith skills

44.3

32.4

46.6

OSWorld-Verified

65.9

58.5

75.6

Agentic coding

SWE-Bench Pro

51.2

36.9

50.2

SWE-Bench Verified

76.0

66.6

77.2

TerminalBench 2.1

51.7

43.4

60.7

SciCode

43.6

43.4

39.8

Multimodal

Charxiv Reasoning

78.8

77.7

78.4

ScreenSpot Pro

75.4

75.9

76.1

OmniDocBench v1.5

75.8

72.5

77.8

MMMU Pro

Safety

CI Memories

Violation (↓): 26.4Coverage: 64.8

Violation (↓): 12.1Coverage: 53.0

Violation (↓): 53.4Coverage: 66.9

Siren AgentDojo

Attack Success Rate (↓): 28.4Utility: 94.2

Attack Success Rate (↓): 25.6Utility: 90.8

Attack Success Rate (↓): 40.3Utility: 92.7

General capabilities and reasoning

IFBench

77.0

76.0

70.8

AIME 2026

94.7

89.2

94.1

GPQA Diamond

83.5

85.7

84.2

Humanity's Last ExamText · No tools

22.0

23.6

23.1

AA-LCR

80.0

68.3

73.3

Beam 128K

65.1

58.2

63.0

For the full model card, please see the Muse Glimmer page on Hugging Face.

For more details about Muse Glimmer evaluations, read the methodology report.

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