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This article is a developer guide to counting and inspecting tokens for LLM prompts, using a single request format across vLLM and Watsonx through LiteLLM. It is useful for budgeting context windows and estimating input costs, and for spotting tokenizer changes after a vLLM update. Token IDs are model-specific, so counts and splits will differ between models and should be checked against each model's own tokenizer.
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Source coveringLiteLLM Blog
Tokenize text across vLLM and Watsonx
LiteLLM Blog4 min read
Choose token counting for prompt budgets or /tokenize to inspect tokens. Use one request format across vLLM and Watsonx through LiteLLM.
Choose a model. Inspect your prompt’s tokens through the same API for vLLM and Watsonx. response.jsonvLLM example Illustrative vLLM response. Your model determines the tokens and IDs. Watsonx uses the same fields with token_ids: null. Tokenize vs. token counting SDK and curl examples PROMPT → TOKEN COUNT, IDS + TEXT /tokenize vs. token counting Check prompt size. Use /utils/token_counter to check context limits or estimate input cost. See how your…
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