Meta Releases Muse Glimmer, a 30-Billion-Parameter Open Agentic Model for Local AI Workflows
Meta has released Muse Glimmer, a 30 billion parameter dense open weight model with over 120K context length optimized for local agentic AI workflows. The mode…
Published on MyPrivateClaw
Aug 10, 2026, 4:10 PM UTC
Coverage date
Aug 10, 2026
Last updated
Aug 10, 2026, 4:10 PM UTC
News summary
Muse Glimmer is a 30 billion parameter dense open weight model with over 120K context length, optimized for local agentic AI workflows on consumer and enterprise hardware. The model is released under an Apache 2.0 license with weights available on Hugging Face. Muse Glimmer can be quantized to approximately 4 bit precision, bringing the language model weights under 20 GB so it fits on consumer GPUs with 24 GB or 32 GB VRAM. The model ships with a DFlash block diffusion speculative decoding drafter that proposes entire blocks of 16 tokens at once, delivering up to 3.1x speedup on NVIDIA RTX 5090. In Meta's evaluations, Muse Glimmer achieves scores of 75.5 on MCP Atlas, 74.6 on DeepSearch QA, and 94.7 on AIME 2026 compared with Gemma4 31B and Qwen3.6 27B. The model can be run through inference stacks including vLLM, SGLang, llama.cpp, MLX, ExecuTorch, and NVIDIA NIM containers.