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Meta open-sources 30B model Muse Glimmer, runs locally on 18GB of memory
Meta open-sources Muse Glimmer, a 30B-parameter dense model that runs on local devices with 18GB of memory, uses the Apache 2.0 license and supports vision. Mark Zuckerberg calls it the strongest agent model at its size and says the weights of the latest foundation model Muse Spark 1.2 will also be open-sourced later. Unsloth already provides a GGUF version of the model along with running and training guides.
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Meta's Muse Glimmer 30B Launches on Fireworks, Targeting Persistent Agents
Fireworks has launched Meta's Muse Glimmer 30B dense model under the Apache 2.0 license, supporting 128K+ token context and native image understanding, targeting persistent agents that require multi-turn tool calling. The model scores 75.5 on MCP Atlas, 74.6 on DeepSearch QA, and 51.2 on SWE-Bench Pro, all higher than the corresponding results of Gemma 4 31B and Qwen 3.6 27B; these benchmark figures are reported by Meta. Fireworks also provides recommended settings of temperature 1.0, top_p 0.95, and top_k 64, and supports adjusting reasoning intensity in the system prompt.
Fireworks has launched Meta's Muse Glimmer 30B dense model under the Apache 2.0 license, supporting 128K+ token context and native image understanding, targeting persistent agents that require multi-turn tool calling. The model scores 75.5 on MCP Atlas, 74.6 on DeepSearch QA, and 51.2 on SWE-Bench Pro, all higher than the corresponding results of Gemma 4 31B and Qwen 3.6 27B; these benchmark figures are reported by Meta. Fireworks also provides recommended settings of temperature 1.0, top p 0.95
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