Muse Glimmer 30B

Muse Glimmer 30B is a dense causal transformer from Meta Superintelligence Labs, paired with a perception encoder for handling visual and video inputs alongside text. The architecture is not a mixture-of-experts design, keeping it suitable for single-machine deployment rather than distributed serving. Meta supplies calibrated GGUF quantizations along with separate vision and speculative-decoding components, letting the model run on consumer hardware with roughly 24GB to 32GB of memory. A 131K context window configuration allows the model to manage long agent sessions, code repositories, and extended document reasoning without truncation.

The model is positioned for local agent use, tool-augmented reasoning, and structured output generation rather than as a general-purpose flagship. Meta's launch evaluation covers an unusually broad agent benchmark suite, and third-party analysis notes that competing dense models like Qwen3.6-27B still edge ahead on some practical agent and multimodal tests in the published comparison. Glimmer's real differentiator is the open-weights release that lets teams self-host, fine-tune, and run speculative decoding locally, which makes it attractive for organizations that need on-premise inference without relying on a hosted endpoint.