Best Meta AI Models in 2026
As of September 15, 2026, the top model in best meta ai models on the BenchLM leaderboard is Muse Spark 1.2 with a score of 70.4.
Bottom line: Meta's Llama models are open-weight and free, but benchmark coverage is still sparse for the newest entries. Llama 4 Maverick leads on coding and reasoning. Llama 4 Scout offers 10M context.
About this ranking
Last verified: September 15, 2026
All Meta Llama models ranked by benchmark performance.
Unless noted otherwise, ranking surfaces on this page use BenchLM’s provisional leaderboard lane rather than the stricter sourced-only verified leaderboard.
Muse Spark 1.2 leads this ranking with a score of 70.4, followed by Muse Spark 1.1 (70.3) and Muse Spark (67.7). The top three are separated by just a few points — any of them would perform well for this use case.
The best open-weight option is Muse Glimmer 30B (ranked #4 with a score of 45). While proprietary models lead, open-weight options are within striking distance for teams willing to trade a few points of performance for full model control.
This ranking uses provisional overall weighted scores from the active scoring formula. For detailed model profiles, click any model name below. To compare two specific models head-to-head, use the "vs #" links.
What changed
Llama 4 Maverick Meta's strongest entry for coding and reasoning tasks.
Llama 4 Scout offers the largest context window of any model at 10M tokens.
Llama 3.1 405B most complete benchmark coverage among Meta models.
Full Rankings (9 models)
Key Takeaways
The top model is Muse Spark 1.2 by Meta with a BenchAlign v5 score of 70.4 and Estimated evidence.
The best open-weight model is Muse Glimmer 30B at position #4.
9 models are included in this ranking.
Score in Context
What these scores mean
Models are ranked by the same overall BenchLM score used across all leaderboards. Comparing within Meta's lineup helps identify which model fits your use case and budget.
Known limitations
This page only shows Meta models. Cross-provider comparison requires the overall or category-specific leaderboards. Newer models may have limited benchmark coverage initially.
Explore More
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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