Meta distills 30B model Muse Glimmer, capable of running agents on a single consumer-grade GPU
Meta distilled the dense 30B model Muse Glimmer from the larger Muse Spark, training it on synthetic agent trajectories in simulated applications; its 4-bit weights are under 20 GB, allowing it to run on a single RTX 5090. On the multi-tool benchmark MCPAtlas it scores 75.5, higher than Gemma4-31B's 54.2 and Qwen3.6-27B's 62.5; however, on OSWorld-Verified it trails Qwen3.6-27B's 75.6 with a score of 65.9.
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AI score 74
The original article provides a side-by-side comparison with models of the same size and the single-GPU deployment threshold, which can be used to gauge where local agent capabilities stand.
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Meta's paper behind, Muse Glimmer 30B, a 30B model distilled from Meta's larger Muse Spark can run AI agents on 1 consumer GPU
Open models small enough for consumer hardware are usually general-purpose and weak at long tool-using tasks. That leaves local agents well behind cloud-hosted ones.
Meta distilled Muse Glimmer, a dense 30B model, from its larger Muse Spark and trained it on synthetic agent runs in mock apps. Its 4-bit weights fit in under 20 GB, so it runs on a single RTX 5090.
On MCPAtlas, a multi-tool test, it scored 75.5 against 54.2 for Gemma4-31B and 62.5 for Qwen3.6-27B. It still trails Qwen3.6-27B on OSWorld-Verified, 65.9 against 75.6.