cross lingual

Multilingual models are uneven across languages, and most candidates only name the obvious cause. The differentiator is the tokenizer: the same sentence can cost a non-English user several times the tokens. Here is the answer.

Every team ships English first, then finds that the retriever, the prompt, the latency budget and the cost model each degrade differently in the next five languages. The applied playbook looks nothing like the model-level answer, and the thing that sinks launches is the eval set nobody built.