Meta Open-Sources Muse Glimmer 30B Agent Model as Zuckerberg Pushes Personal-Superintelligence Vision

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open-source multimodal agentic quantization local-inference meta

Summary

Meta open-sourced Muse Glimmer, a 30B-parameter multimodal agentic model under Apache 2.0, optimized for local tool use and coding with 4-bit quantization fitting under 20GB for consumer GPUs. Zuckerberg also promised open-weight Muse Spark 1.2 and a $1B community fund for data-center regions.

Meta released Muse Glimmer, a 30B-parameter dense multimodal model under Apache 2.0, tuned for local agentic tool use, coding, and LLM-as-judge with a 131K context and support for 100+ languages. 4-bit quantization compresses it under 20GB so it runs on a single consumer GPU, hitting 3.1x speedup on RTX 5090 via speculative decoding. Meta paired the drop with a 6,500-word Zuckerberg essay promising open weights for Muse Spark 1.2 in the coming weeks, defending model distillation, and a $1B community fund for regions hosting Meta data centers. Source: https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model
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Meta Superintelligence Lab releases Muse-Glimmer-30B, a 30B-parameter causal language model with a perception encoder, optimized for autonomous agentic tasks on consumer hardware with reliable tool use, multi-step reasoning, and multimodal input.