Meta ships Muse Glimmer, a 30B open agent model

Meta Superintelligence Labs released Muse Glimmer on August 10, a 29.6 billion-parameter model for local AI agents licensed under Apache 2.0, per Meta's technical blog.

For about a year, local models couldn't reliably call a tool twice in a row. Muse Glimmer scores 51.2% on SWE-Bench Pro, the first credible open substitute for a hosted agent loop.

Quantized to roughly 4-bit, the model fits under 20GB and runs on 24 to 32GB of consumer hardware. AMD published a same-day guide for Ryzen AI Max and Radeon.

It was distilled from April's Muse Spark and built for always-on agents, naming OpenClaw among the supported orchestrators. Meta benchmarks it against Gemma4-31B and Qwen3.6-27B.

Open-source tooling outran Meta's own release. An Unsloth GGUF appeared on Hugging Face within hours, while Meta's post lists Ollama, LM Studio, llama.cpp, MLX, ExecuTorch, vLLM and SGLang as "coming soon." One Reddit commenter warned that template bugs cause most "can't tool-call" complaints.

DFlash, Meta's speculative-decoding drafter, proposes whole blocks of tokens for the base model to verify. That's 3.1x faster on an RTX 5090, but only 1.8x on M5 Max and 1.5x on M4 Max, per Meta's blog.

That "3x faster" framing assumes Nvidia hardware; on last-gen Apple silicon you get roughly half the CUDA benefit. I'm on a Mac, so that gap decides whether this replaces my hosted loop or just backs it up.

Alexandr Wang said on X that Meta will open-weight Muse Spark 1.2 "soon." That's the 1M-context frontier model that launched August 5, per the Wall Street Journal's "coming weeks" timeline.

An independent harness measured DeepSeek-V4-Flash-0731 at 82.7% on Terminal-Bench 2.1 that same day, up from 61.8% for the preview, at $0.14 per million input tokens. HN commenters used the price gap to argue against buying inference hardware at all.

Pull the Unsloth GGUF, check the chat template against your tool schema, then see if it holds as a free fallback for rate limits.