LFM2.5-8B-A1B doubles its tokenizer vocab and cuts on-device decoding time up to 3.7x
maximelabonne · x · 2026-07-22
A report and blog post describe how LFM2.5-8B-A1B upgraded its tokenizer vocabulary from 65K to 128K to better handle languages that had been split too finely.
The result was much shorter token sequences and faster on-device decoding:
- Thai: 4.0× fewer tokens
- Vietnamese: 2.6× fewer tokens
- Hindi: 2.4× fewer tokens
- Estimated 2.2–3.7× faster per-character decoding on device for these languages
The post frames this as a recipe for upgrading a pretrained model's tokenizer in place.
Related event: Liquid AI Expands LFM2 Tokenizer to 128K for Multilingual Efficiency(3 posts)→
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