Meta Superintelligence Labs ships its debut model, Muse Spark — closed-weight, and not the Llama playbook
Meta introduced Muse Spark, the first model out of Meta Superintelligence Labs and the first in its Muse family: a natively multimodal reasoning model with tool use, visual chain-of-thought, and a Contemplating mode that orchestrates multiple parallel reasoning agents.
Unlike the Llama line it is proprietary, rolling out through the Meta AI app, meta.ai, and Ray-Ban and Oakley glasses. Meta describes RL training that maximizes correctness subject to a thinking-time penalty, producing thought compression on evaluations like AIME. Published numbers show it competitive but not dominant: 75.1 on Terminal-Bench 2.0 and 93.5 on IPhO 2025 Theory, but 42.5 on ARC-AGI-2 against Gemini 3.1 Pro's 76.5.
WHY IT MATTERS
A reorganized lab's first output, and a strategy reversal: Meta's frontier models are now closed-weight product differentiators, with reasoning-token efficiency rather than raw scale as the headline claim.
