Giulianno Vollmer’s Metis-1.6 technical report describes two language models built from scratch: Praxis, with 2.94 billion parameters, and Logos, with 10.23 billion. The report says Logos placed seventh among 17 models across 40 benchmarks, and second among 30 models in mathematics; it also notes weaknesses in code, instruction following and long-context tasks.
Vollmer details several training problems, including an optimizer that never ran and a length-reward bug that could penalize correct, lengthy answers. The report says Logos was trained on 1.02 trillion tokens and was not intended to compete with frontier models.
Why it matters
For developers considering smaller models, the report offers benchmark results and specific training lessons, but its own findings show Logos is weak at code and long-context work; independent validation is not documented here.
