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**Authors:** Meta Superintelligence Lab **Model Release Date:** August 2026 **License:** Apache 2.0 > [!NOTE] This model card is for the lightweight "drafter" model for Muse Glimmer 30B, based on DFlash. The DFlash block-diffusion model predicts entire blocks of 16 tokens in a single forward pass. The main model then verifies these proposals in parallel, accepting correct tokens and correcting wrong ones. This technique lets Muse Glimmer generate text significantly faster than standard token-by-token generation while producing identical output quality. Muse Glimmer is a 30-billion-parameter causal language model with a dedicated perception encoder, distilled from Muse Spark and purpose-built for autonomous agentic tasks on consumer hardware. The model integrates multi-step reasoning, reliable tool use, multimodal understanding, and failure recovery into a single model that runs locally without requiring cloud infrastructure or network access.

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**Authors:** Meta Superintelligence Lab **Model Release Date:** August 2026 **License:** Apache 2.0 > [!NOTE] > This repo contains GGUF conversions of `meta-models/Muse-Glimmer-30B` for llama.cpp: two quantized text builds, a perception encoder for image input, and a DFlash drafter for speculative decoding. > Everything you need to install, download and serve them is on this page. No bf16 GGUF is published here — use the base repo if you need full precision. Muse Glimmer is a 30-billion-parameter causal language model with a dedicated perception encoder, distilled from Muse Spark and purpose-built for autonomous agentic tasks on consumer hardware. The model integrates multi-step reasoning, reliable tool use, multimodal understanding, and failure recovery into a single model that runs locally without requiring cloud infrastructure or network access.

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