Muse Glimmer 30B: An On-Device Agentic Model

Key points

• Muse Glimmer integrates multi-step reasoning, reliable tool use and failure recovery into a single model that runs locally on consumer devices without requiring cloud infrastructure.1
• The model accepts text and image inputs and produces text outputs, was trained on data from over a hundred languages, and is quantized to approximately 4-bit precision for efficient single-GPU inference.1
• Muse Glimmer achieves state-of-the-art performance for its size class on agentic benchmarks, setting a new standard compared to the models of its size: Gemma4-31B and Qwen3.6-27B on tool use, multi-step planning, and agentic task completion.1
• We release the model under the Apache 2.0 license to foster open-source development of capable, safe, local AI agents.1

Sources (2)

• [1]Muse Glimmer 30B: An On-Device Agentic Model
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 17, 11:05 AM

  We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware.

  Muse Glimmer integrates multi-step reasoning, reliable tool use and failure recovery into a single model that runs locally on consumer devices without requiring cloud infrastructure.

• [2]Muse Glimmer 30B: An On-Device Agentic Model
  Hugging Face Daily Papers · Oct 17, 12:00 AM · same content

Extractive summary: sentences quoted from the sources.