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New Models AI Minute Newsroom 2026-08-10

Meta's new model is small enough to live on your own machine — and it is the first thing Superintelligence Labs has given away

Meta's new model is small enough to live on your own machine — and it is the first thing Superintelligence Labs has given away

Meta released Muse Glimmer on Monday, a 30-billion-parameter model built to run local agents on hardware people already own, under a permissive Apache 2.0 licence. It is a dense model with a dedicated vision encoder rather than a mixture-of-experts, distilled from the much larger Muse Spark, and it carries a 131,000-token context window. At full precision it needs more than 55 GB of memory; quantised to four bits it fits on a 24 GB consumer graphics card, and Meta reports about 233 tokens per second on an RTX 5090 with speculative decoding, roughly three times the unaccelerated rate. The published scores are strong for the size class — 94.7% on AIME 2026, 83.5 on GPQA Diamond, 76.0 on SWE-Bench Verified — and on agent-specific tests the gap is wide: 75.5 on MCP Atlas against 54.2 for Google's Gemma4-31B and 62.5 for Qwen3.6-27B. It is not a clean sweep. Qwen3.6-27B still edges it on SWE-Bench Verified at 77.2, and beats it on OSWorld-Verified and TerminalBench 2.1. Audio input and output are unsupported, and Meta's own card says the model should not be used by anyone under 18.

Why it mattersTwo things happened at once here. The first is technical: a model that scores in this range on tool use and multi-step tasks now runs on a single gaming GPU, offline, with no per-token bill and no data leaving the room. That changes who can build an agent — a school, a clinic, a small firm with one workstation — and it changes what an agent is allowed to touch, because nothing has to be uploaded to anyone. The second is political. This is the first open model from Meta Superintelligence Labs, and Mark Zuckerberg used the launch to attack OpenAI and Anthropic for keeping their best systems closed, and to press Washington to loosen the training-data rules he says put American labs behind. That argument has teeth right now for an uncomfortable reason: the leading open-weight models of the past year have mostly come out of China — Kimi K3, Qwen3.8-Max, DeepSeek V4-Flash — while the top US systems stayed locked. Meta is betting it can be the American exception, and it has picked the most permissive licence available to prove the point.
#Coding#AI Agents

✓ Verified · 5 sources

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