Bolmo’s architecture unlocks efficient byte‑level LM training without sacrificing quality

Enterprises that want tokenizer-free multilingual models are increasingly turning to byte-level language models to reduce brittleness in noisy or low-resource text. To tap into that niche — and make it practical at scale — the Allen Institute of AI (Ai2) introduced Bolmo, a new family of models that leverage its Olmo 3 models by “bytefiying” them and reusing their backbone and capabilities.

The company launched two versions, Bolmo 7B and Bolmo 1B, which are “the first fully open byte-level language model,” according to Ai2. The company said the two models performed competitively with — and in some cases surpassed — other byte-level and character-based models.

Byte-level language models operate directly on raw UTF-8 bytes, eliminating the need for a predefined vocabulary or tokenizer. This allows them to handle misspellings, rare languages, and unconventional text more reliably — key requirements for moderation, edge deployments, and multilingual applications.

For enterprises deploying AI across multiple languages, noisy user ...