---
type: "raw_signal"
id: "meta-released-muse-glimmer-30b-an-open-weight-4e952f"
slug: "meta-released-muse-glimmer-30b-an-open-weight-4e952f"
title: "Meta released Muse Glimmer 30B , an open-weight agentic model under Apache 2.0."
description: "Meta introduced Muse Glimmer 30B, an open-weight causal language model with a perception encoder designed for autonomous agentic tasks on consumer hardware."
retrieval_nugget: "Meta introduced Muse Glimmer 30B, an open-weight causal language model with a perception encoder designed for autonomous agentic tasks on consumer hardware."
observed_at: "2026-10-19"
record_date: "2026-10-19"
date_kind: "observed_at"
why_it_matters: "Source: https://ai.meta.com/research/publications/muse-glimmer-30b-an-on-device-agentic-model"
novelty: "notable"
verification_level: "source-linked"
signal_type: "release"
source_platform: "ai.meta.com"
topics: ["tool-use"]
entities: ["Meta","Muse Glimmer 30B","Apache License 2.0"]
related_patterns: []
source_url: "https://ai.meta.com/research/publications/muse-glimmer-30b-an-on-device-agentic-model"
source_urls: ["https://ai.meta.com/research/publications/muse-glimmer-30b-an-on-device-agentic-model"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "signal:meta-released-muse-glimmer-30b-an-open-weight-4e952f"
status: "published"
visuals: []
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
routes: {"html":"https://newruntime.com/signals/meta-released-muse-glimmer-30b-an-open-weight-4e952f/","markdown":"https://newruntime.com/signals/meta-released-muse-glimmer-30b-an-open-weight-4e952f.md","json":"https://newruntime.com/signals/meta-released-muse-glimmer-30b-an-open-weight-4e952f.json"}
---

# Meta released Muse Glimmer 30B , an open-weight agentic model under Apache 2.0.

## Retrieval answer

Meta introduced Muse Glimmer 30B, an open-weight causal language model with a perception encoder designed for autonomous agentic tasks on consumer hardware.

Meta introduced Muse Glimmer 30B, an open-weight causal language model with a perception encoder designed for autonomous agentic tasks on consumer hardware. Its research page says the model combines multi-step reasoning, tool use, and failure recovery, and runs locally without cloud infrastructure. It accepts text and image inputs and produces text outputs; Meta says it is quantized to approximately 4-bit precision for single-GPU inference and released under Apache 2.0. Meta also reports state-of-the-art results for its size class on agentic benchmarks, including tool use, multi-step planning, and task completion. The announcement does not provide benchmark conditions or independent validation in the supplied material.

Source: https://ai.meta.com/research/publications/muse-glimmer-30b-an-on-device-agentic-model

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

## Continue in the graph

Next records for an agent, linked to their Markdown twins. Replace `.md` with `.json` for structured fields, including `next_reads`.

- topic hub: [Tool Use](https://newruntime.com/topics/tool-use.md): Explore the tool-use topic hub.
- collection: [Raw Signals](https://newruntime.com/signals.json): Open every source-linked raw signal.
- collection: [Source Ledger](https://newruntime.com/source-ledger.json): Inspect the public source evidence graph.
- whole graph: [discovery graph](https://newruntime.com/discovery-graph.json) (typed nodes and edges) and [site index](https://newruntime.com/site-index.md)