[Townley]

Using Chinese could lead to a small amount of gains, but it's nowhere near as drastic as you'd think

Putting aside the question of whether English's larger training corpus would be a dimension of quality: content is "tokenized" before the model sees it. The "~4 English chars/token" rule isn't a strategy to optimize around because in practice, many English words become one token, the same way Chinese words do.

"I love you" and "我爱你" both tokenize down to 3 tokens. So no efficiency gains from a Chinese translation. "Telephone" is just one token, and "电话" (Chinese word for telephone that spans 2 characters) also gets condensed into one token. Sometimes there are minor gains, like "经济" being one token but "economy" being two. But it doesn't end up materializing in the gain you'd hope for by increasing meaning-per-character.

You can play around with OpenAI's tokenizer here. Great for getting particular about how to save tokens in prompt and tool definitions https://platform.openai.com/tokenizer