# Meta — Muse Glimmer

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- This model's page: https://forck.live/models/muse-glimmer-30b
- Meta's page: https://forck.live/company/meta
- Every model: https://forck.live/models
- Catalogue: https://forck.live/llms.txt

## Model

- Name: Muse Glimmer
- Company: Meta (meta.com)
- Launch post: Introducing Muse Glimmer: An Open Agentic Model That Runs on Your Device — https://forck.live/items/7279-introducing-muse-glimmer-an-open-agentic-model-that-runs-on-your-device
- Announced: 2026-08-10
- Launch source: https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model
- Launch chosen by: a person, pinned in the model registry
- Released (per models.dev): not stated
- Listed (per OpenRouter): 2026-08-09
- Open weights: not stated
- Posts about it: 1
- Outlets named under its posts: 0
- Also written: Muse Glimmer 30B
- OpenRouter id: meta/muse-glimmer-30b — https://openrouter.ai/meta/muse-glimmer-30b
- Licence: Apache 2.0 — from https://forck.live/items/7279-introducing-muse-glimmer-an-open-agentic-model-that-runs-on-your-device

## Posts about it

_Meta's own posts whose title names Muse Glimmer, and its launch post, in the record's order: dated newest first, undated last. The record reads the newest 50 first-party posts mentioning the model, every company's together, so a model mentioned more often than that lists the newest of them._

Every entry is one first-party announcement, and carries the same eight fields
in this order before any others:

    Company · Announced · Category · Coverage · Announcement · Group · Source · Record

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is this site's page for it. Both are safe to cite.

`Coverage` is a number of outlets, or `not counted` — which means this record
reached no count of its own, never that nobody wrote about it.

`Category` is this tracker's own analysis, and is authoritative wherever it is
stated. `not stated` means either that nothing has analysed the post yet or
that the analysis placed it outside this taxonomy; neither is a verdict about
the announcement.

`Announcement` is whether the post is news of something the company did, rather
than a how-to, a customer story, a changelog listing or a staffing note.

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entry itself so it holds where the groups are headings and where they are not.
One of: `models`, `covered`, `announcements`, `routine`.

Anything after `Record` is held detail that only some announcements carry.

### Meta — Introducing Muse Glimmer: An Open Agentic Model That Runs on Your Device

- Company: Meta (meta.com)
- Announced: 2026-08-10
- Category: open-weight-release
- Coverage: not counted
- Announcement: yes
- Group: models
- Source: https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model
- Record: https://forck.live/items/7279-introducing-muse-glimmer-an-open-agentic-model-that-runs-on-your-device
- Subject: Muse

Meta introduces Muse Glimmer, a 30-billion-parameter agentic model released under the Apache 2.0 license, optimized for always-on local agent workflows on a device like a Mac or PC with a single consumer GPU.

## Who reported on it

_This record names no outlet that reported on these posts._

## Where it runs

_Other companies' own announcements naming Muse Glimmer and Meta — each is that company's post, not Meta's._

### Hugging Face — Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta

- Company: Hugging Face (huggingface.co)
- Announced: 2026-10-15
- Category: open-weight-release
- Coverage: not counted
- Announcement: yes
- Group: models
- Source: https://huggingface.co/blog/meta-muse-spark-open
- Record: https://forck.live/items/23000-welcome-muse-spark-open-open-weight-frontier-multimodal-mixture-of-experts
- Subject: Platform

Meta released Muse Spark Open, an open-weight multimodal mixture-of-experts model with approximately 816 billion total parameters and about 42 billion active per token, supporting text, images, audio, and video input. The model is optimized for agentic coding tasks such as reading codebases, writing and debugging code, and calling tools, and can also process screenshots, voice notes, and screen recordings. It uses 256 experts per MoE block with 8 selected per token, and offers a context window of up to one million tokens. The BF16 checkpoint requires 4 nodes of 8 H200 GPUs, while an NVFP4 checkpoint runs on a single B200 node with negligible accuracy loss.

### Hugging Face — Meta is back with Muse Glimmer: local, agentic, multimodal, and open source

- Company: Hugging Face (huggingface.co)
- Announced: 2026-08-10
- Category: new-model
- Coverage: not counted
- Announcement: yes
- Group: models
- Source: https://huggingface.co/blog/muse-glimmer
- Record: https://forck.live/items/3747-meta-is-back-with-muse-glimmer-local-agentic-multimodal-and-open-source
- Subject: Platform

Meta released Muse Glimmer, a 30B parameter multimodal model distilled from Muse, licensed under Apache 2.0, designed for local agentic use cases like coding, document analysis, and personal assistants. It includes a 2B vision encoder and a 28B text decoder with hybrid attention and Gated Grouped-Query Attention. Support for transformers, llama.cpp, vLLM, and Inference Endpoints is provided day-0. Benchmarks show competitive performance in agentic and multimodal tasks against models like Gemma4-31B and Qwen3.6-27B.

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Record: https://forck.live/models/muse-glimmer-30b
Catalogue: https://forck.live/llms.txt
Current issue: https://forck.live/feed.md
