Meta publishes the Muse Glimmer 30B technical report: a dense model distilled from Muse Spark for a 32 GB budget, leading similar-size open models on tool use

Why it matters

【Key points】

Meta published the technical report for Muse Glimmer 30B on Oct 19 (19:33 UTC). The open-weight model first shipped on Aug 10, and Meta Superintelligence Labs pitches it as a local agent model for consumer hardware. The report is the first detailed description of how it was built.

Architecture: a dense transformer of about 29.6B parameters plus a ~1.8B perception encoder (text and image in, text out), 52 layers, grouped-query attention with only 2 KV heads, three sliding-window layers (2,048 tokens) for every global layer, and 128K+ context. Meta says that under a fixed 32 GB memory budget, dense configurations were 2–2.5× more compute-efficient than its MoE alternatives, so it chose dense.

Training: pre-training uses logit distillation from Muse Spark, followed by SFT, reinforcement learning and on-policy distillation. Meta released full-precision and ~4-bit weights plus a DFlash head for speculative decoding, under Apache 2.0, and says the model runs at practical speeds on a single RTX 5090.

Results (Meta's own tests, high reasoning): 75.5 on MCPAtlas versus 54.2 for Gemma4-31B and 62.5 for Qwen3.6-27B, and 51.2 on SWE-Bench Pro. It still trails Qwen3.6-27B on TerminalBench 2.1, OSWorld-Verified and GDPval-AA.

【Verifiable】

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

Meta announcement: https://x.com/AIatMeta/status/2112265822274302066

Weights: https://huggingface.co/meta-models/Muse-Glimmer-30B

【Our read】

1. The value is the recipe: distilling a 30B model directly from a frontier teacher and choosing a dense design for a 32 GB budget gives builders of local agent models a reproducible blueprint.

2. All scores are self-reported. The tool-use lead is clear, but it does not win across coding and computer-use tests, and some developers note the table omits the newer Qwen3.8-27B.

3. The model itself shipped two months ago. This report adds technical detail rather than a new model.