RT by @ylecun: Meta returns to open weights: Muse Glimmer, its first open-weights release since…

TL;DR - Meta released Muse Glimmer, a 30B dense open-weights model and its first under Apache 2.0, scoring 35 on the Artificial Analysis Intelligence Index — 21 points above Llama 4 Maverick and its first open release in 16 months. It signals Meta re-entering the open-weights race with a permissive license, though it trails Chinese open models like Qwen3.6 27B on the intelligence-vs-parameters frontier.

• License shift: First Meta model under Apache 2.0 rather than the restrictive Llama License; Openness Index of 44. It forms a two-tier lineup alongside the proprietary flagship Muse Spark 1.2 (xhigh, 57).
• Efficient architecture: 30B dense (incl. ~1.8B vision encoder), ~60 GB BF16 / ~18 GB in 4-bit. Hybrid attention with three sliding-window layers per global layer caps KV cache at ~1.8 GB at 128K context — runnable at full context on one H100 (BF16) or an RTX 5090/high-spec MacBook (4-bit).
• Punches above weight on raw intelligence: 5 points above same-size Gemma 4 31B and effectively matches 1T-parameter Kimi K2.5 (36) with 33x fewer parameters.
• Weak on agentic knowledge work and calibration: 953 Elo on GDPval-AA v2 (below the 1,000 human baseline) vs. 1141 for Qwen3.6 27B; AA-Omniscience Index of -33 driven by an 82% hallucination rate (vs. 49%). Agentic tool use is the exception — 24% on Tau3-Banking, best in its class.