Meta returns to open weights: Muse Glimmer, its first open-weights release since — Intel

Terms in this piece · Glossary

open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.

Why it matters

An Apache-2.0 30B model that matches a 1T-parameter peer and fits on one GPU at full changes what is realistic to self-host.

Key quotes

“Muse Glimmer (high) arrives 16 months after Llama 4, scoring 21 points above Llama 4 Maverick (14), Meta's last open weights release.”
ArtificialAnlys

“Every prior Meta open release shipped under a Llama License; Muse Glimmer uses Apache 2.0, placing almost no restrictions on commercial use or derivatives”
ArtificialAnlys

“At 30B parameters, Muse Glimmer scores 5 points above Gemma 4 31B (Reasoning, 30) at the same size, and effectively matches 1T total parameter Kimi K2.5 (Reasoning, 36) with 33x fewer parameters.”
ArtificialAnlys

“This means the model can run at full context on a single H100 at BF16 precision, or on a higher-spec MacBook or RTX 5090 at 4-bit, with more breathing room if the vision encoder is not required”
ArtificialAnlys

“its AA-Omniscience Index of -33 is low for its intelligence level, driven by an 82% hallucination rate (Qwen3.6 27B: 49%) rather than accuracy, where it matches its peers”
ArtificialAnlys