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Meta releases Muse Glimmer weights for local agents

Written by an AI model from the linked sources and checked against them by a second model. How we work

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Meta Superintelligence Labs has put Muse Glimmer, a 30-billion-parameter model, on Hugging Face under Apache 2.0, weights and docs included. The target is always-on agents running on a Mac or a PC with a single consumer GPU: the model plans tasks, calls tools, and recovers when those tools fail. It handles more than 100 languages and has switchable reasoning depth.

At full precision it needs more than 55 GB of memory. Quantization squeezes the language model below 20 GB. For the K-Quant-17GB build, Meta claims 3.1x faster decoding on an RTX 5090, 1.8x on an M5 Max, and 1.5x on an M4 Max.

Meta benchmarks the results against Gemma4-31B and Qwen3.6-27B. Mark Zuckerberg said the weights for Muse Spark 1.2 are coming soon.

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