{"slug":"agenttools-hub-vercel-app-api-v1-dev-token-estimator-c37f92","title":"Estimate how many tokens a text consumes for each major model family (GPT, Claud","host":"agenttools-hub.vercel.app","method":"GET","resource":"https://agenttools-hub.vercel.app/api/v1/dev/token-estimator","category":"market","description":"Estimate how many tokens a text consumes for each major model family (GPT, Claude, Gemini, Llama, DeepSeek) using a character/word heuristic that is within ~10% of real BPE tokenizers — enough for context budgeting and cost math, with zero dependencies. Use this when an agent needs to approximate to","price_listed":0.001,"price_asked":0.001,"state":"answering","state_label":"Answering","checks_7d":1,"answered_7d":1,"latency_ms_median":254,"reported_calls_30d":3,"reported_payers_30d":1,"networks":["eip155:8453"],"badge":"unverified","paid_checks_7d":0,"paid_ok_7d":0,"example_input":{"method":"GET","queryParams":{"text":"The quick brown fox jumps over the lazy dog. Pack my box with five dozen liquor jugs."},"type":"http"},"output_schema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{"input":{"additionalProperties":false,"properties":{"method":{"enum":["GET"],"type":"string"},"queryParams":{"properties":{"text":{"description":"Text","type":"string"}},"required":["text"],"type":"object"},"type":{"const":"http","type":"string"}},"required":["type","method"],"type":"object"},"output":{"properties":{"example":{"type":"object"},"type":{"type":"string"}},"required":["type"],"type":"object"}},"required":["input"],"type":"object"},"history":[{"day":"2026-10-02","reachable":true,"status":402,"valid_402":true,"asked_usdc":0.001,"price_match":true,"latency_ms":254,"error":null}],"description_full":"Estimate how many tokens a text consumes for each major model family (GPT, Claude, Gemini, Llama, DeepSeek) using a character/word heuristic that is within ~10% of real BPE tokenizers — enough for context budgeting and cost math, with zero dependencies. Use this when an agent needs to approximate token counts per LLM family, ±10%.","last_updated":"2026-10-02T00:11:21.48Z","schemes":["exact"]}