Meta Releases Muse Glimmer: A 30B Open-Weight Model for Local Agents
AIatMeta · reddit · 2026-08-10
Meta has officially released Muse Glimmer, a new open-weight model designed specifically for local agent workflows. The 30B dense model supports multimodal input (interleaved text and images) and is available under the permissive Apache 2.0 license.
Key Specs & Features:
- On-device Optimization: While full precision requires 55GB+ RAM, the model can be quantized to 4-bit, fitting under 20GB. This allows it to run on consumer hardware (24GB/32GB VRAM) alongside KV cache and speculative decoding.
- Speculative Decoding: Ships with a lightweight DFlash-based drafter that proposes token blocks verified in parallel, significantly increasing speed without quality loss.
- Agentic Capabilities: Trained for end-to-end task completion (strong performance on SWE-Bench, DeepSearch QA), precise function calling over long workflows, and robust failure recovery (diagnosing and retrying failed tool calls).
Weights are live on Hugging Face, with upcoming support for Ollama, llama.cpp, vLLM, and hardware-level optimizations across AMD, Intel, NVIDIA, and more.
Related event: Meta Open-Sources 30B Muse Glimmer for On-Device Agents(108 posts)→
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