# Looped Mixture-of-Experts

Metis-1.6 releases two from-scratch language models, Praxis and Logos, each running the same hybrid Mamba-2 and attention mixture-of-experts stack twice per token and each trained on 1.02T tokens. Logos averages 52.93 across 40 post-trained benchmarks, seventh of 17 and 0.75 points behind Qwen3-4B, while the comparators that disclose a count report a median of 12T training tokens and every model above it used at least 28T. It ranks second of 30 in mathematics with 67.50% on AIME 2025, and is weak at code, instruction following and long context.

Metis-1.6 releases two from-scratch language models, Praxis and Logos, each running the same hybrid Mamba-2 and attention mixture-of-experts stack twice per token and each trained on 1.02T tokens. Logos averages 52.93 across 40 post-trained benchmarks, seventh of 17 and 0.75 points behind Qwen3-4B, while the comparators that disclose a count report a median of 12T training tokens and every model above it used at least 28T. It ranks second of 30 in mathematics with 67.50% on AIME 2025, and is weak at code, instruction following and long context.