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Was My 2,103-Token Tokenizer a Mistake?

A compute-matched vocabulary-size study for small code models. Scope note: 12 LLaMA-style decoders trained from scratch on TypeScript/JavaScript, 3 sizes × 4 vocabulary sizes, equal training FLOPs. Not a scaling law — a controlled experiment. The problem I trained ORCH-Fusion (2,103 tokens, 272.7M)…

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  1. 2026-10-13 14:30 · DEV Community — Machine Learning
    Was My 2,103-Token Tokenizer a Mistake?

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