As of: 2026-11-13 13:49 CET.
Researched and written by AI agents (Claude Opus 5.5 in Claude Code), with a human editor. How we work: https://postcutoff.com/about/
Canonical page: https://postcutoff.com/m/muse-glimmer-30b/

# Muse Glimmer 30B

Meta, Muse family. Status: current. Type: language model. Released: 2026-08. Training cutoff: 2026-01.

## How to call it

| Provider | Model id | Endpoint | Docs |
|---|---|---|---|
| Hugging Face |  |  | https://huggingface.co/meta-models/Muse-Glimmer-30B |
| OpenRouter | `meta/muse-glimmer-30b` |  | https://openrouter.ai/meta/muse-glimmer-30b |

## Pricing

- Input: $0.30 per 1M tokens
- Output: $1.20 per 1M tokens
- Unit as published: per 1M tokens (USD) on OpenRouter; open weights free to self-host
- Source: https://openrouter.ai/meta/muse-glimmer-30b
- Last checked: 2026-09-29

## Specs

- Input: text, image
- Output: text
- Context window: 131,072 tokens
- Max output: not published
- Open weights: yes
- Licence: apache-2.0

## What it has not seen

- Published training cutoff: 2026-01 (January 2026).
- AI events after it on Post-Cutoff: 1,945 (444 major, 85 historic), as of 2026-11-13.
- Already missing at launch: 241.
- Briefings of the news since January 2026: https://postcutoff.com/briefings/cutoff-2026-01-s.md (short), https://postcutoff.com/briefings/cutoff-2026-01-m.md (medium), https://postcutoff.com/briefings/cutoff-2026-01.md (full).
- Its card, with five things it has never heard of: https://postcutoff.com/you/muse-glimmer-30b/

## What stands out

- Meta open weights under Apache 2.0: ~29.6B dense text+image model released Apache 2.0 (Llama used a custom community license), with llama.cpp / MLX / ExecuTorch integrations. Source: https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model
- Local agents on one consumer GPU: Quantized to under 20GB for 24-32GB consumer GPUs/Macs; bundled DFlash drafter for speculative decoding gives ~3.1x speed-up on RTX 5090. Source: https://huggingface.co/meta-models/Muse-Glimmer-30B
- Agentic focus for its size: Optimized for multi-step reasoning, reliable tool use and failure recovery; Meta benchmarks it as competitive with Gemma4-31B and Qwen3.6-27B on agentic/coding evals. Source: https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model

## Notes

Released early Aug 2026 (exact day not verified). HF org is meta-models, not meta-llama. No first-party Meta API id verified.

Open-weight agentic/vision model for local deployment.

```python
from transformers import pipeline
pipe = pipeline("image-text-to-text", model="meta-models/Muse-Glimmer-30B")
```

Sources: https://huggingface.co/meta-models/Muse-Glimmer-30B , https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model

Model page: https://postcutoff.com/m/muse-glimmer-30b/