Tokens
Tokens are the chunks of text a language model reads and writes; pricing and context limits are measured in them, not words or characters.
A token is roughly a word-piece — common words are one token, rarer words and code split into several. Models process and bill by tokens, so token counts, not word counts, drive both cost and context limits.
Different models tokenize the same text differently, so the same prompt can cost a different number of tokens across providers. For accurate budgeting, count tokens with the target model’s tokenizer rather than estimating.
Because both input and output are billed per token (and reasoning tokens count as output on some models), understanding token usage per route is the foundation of any cost-optimization effort.