{"openapi":"3.1.0","info":{"title":"Token Counter","version":"0.1.0","description":"Count the LLM tokens in text for a given model or encoding — exact for OpenAI and open models, labelled-approximate for Claude & Gemini.","x-guidance":"Count the LLM tokens in text for a given model or encoding — exact for OpenAI and open models, labelled-approximate for Claude & Gemini. Each operation is an HTTP POST to its /v1/<operation> path with a JSON request body (see each operation's requestBody schema) and returns a JSON response. Endpoints are paid per successful call via x402 or MPP (USDC on Base); an unpaid request returns 402 with payment metadata in the WWW-Authenticate header.","contact":{"email":"hello@openverbs.com"}},"x-discovery":{"ownershipProofs":["0xb1401a71756f51464a9962db12f1eb3e9522490cd20010b06d00cf7b7770acfd5f79721f9dfdf2643f8cecd29af3bde9ec133941a386042b32d9886053a70de61b","0xc1c1f11793e18a00fcb7072421f26e89fb75b6aa517fa84370564991f4b10efa024f6f57e4e67eefd20cf46cc01fc5a62d793fa8fbcda04f26c946a3433d73f91b","0x676b474af0ef9ed4809b5d12d2e789b36e52d56215b21f601d71f76620e36ec630347116a7b2b349a3c3681e5db0fbfa76c4169a676b6d6f27864d0e5017284a1c","0xc2ab96522515ed9e9bc4f1a241b774bd48df42e951ddbf7f6aa8fc76f5a96a20421703e1ec402ce7eb1e4eabea3b6e4e4129cf39d56ea91cf4fcf38561fc94fc1c"]},"servers":[{"url":"https://tokens.openverbs.com"}],"paths":{"/health":{"get":{"summary":"Health check","security":[],"responses":{"200":{"description":"Healthy","content":{"application/json":{"schema":{"type":"object","properties":{"ok":{"type":"boolean"},"service":{"type":"string"},"version":{"type":"string"}}}}}}}}},"/v1/count":{"post":{"summary":"Count tokens","description":"Count the LLM tokens in text for a given model or encoding — exact for OpenAI and open models (Llama, Mistral, Qwen, Gemma, DeepSeek, Command-R); labelled-approximate for Claude & Gemini. Paid endpoint (x402 + MPP). Price: $0.004000 USDC per successful payment.","tags":["count llm tokens","token count api","count text tokens","estimate prompt tokens","model tokenizer count","openai token count"],"requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","properties":{"text":{"type":"string","maxLength":100000,"description":"The text to tokenize. Empty string counts as 0 tokens."},"model":{"type":"string","minLength":1,"maxLength":100,"description":"LLM model name, e.g. \"gpt-4o\", \"llama-3.1-70b\", \"claude-3-5-sonnet\". Resolved to its tokenizer. Defaults to gpt-4o. Supported families: o200k_base, cl100k_base, p50k_base, r50k_base, llama3, llama2, mistral, qwen, gemma, deepseek, command-r, claude, gemini."},"encoding":{"type":"string","enum":["o200k_base","cl100k_base","p50k_base","r50k_base"],"description":"Explicit OpenAI BPE encoding. Overrides \"model\" and is always exact. Defaults to o200k_base."}},"required":["text"],"additionalProperties":false}}}},"responses":{"200":{"description":"The token count (`tokens`) of the text under the resolved `tokenizer`, the echoed `model`, `characters`, and `exact` (false with a `note` for Claude/Gemini approximations or an unknown model).","content":{"application/json":{"schema":{"type":"object","description":"The token count (`tokens`) of the text under the resolved `tokenizer`, the echoed `model`, `characters`, and `exact` (false with a `note` for Claude/Gemini approximations or an unknown model)."}}}},"400":{"description":"Invalid request; no payment is attempted"},"402":{"description":"Payment required; x402/MPP metadata returned in headers"},"502":{"description":"Upstream provider error after payment verification"}},"x-payment-info":{"amount":"4000","currency":"0x20c000000000000000000000b9537d11c60e8b50","description":"Count the LLM tokens in text for a given model or encoding — exact for OpenAI and open models (Llama, Mistral, Qwen, Gemma, DeepSeek, Command-R); labelled-approximate for Claude & Gemini.","method":"tempo","preferredOffer":"mpp-tempo","price":{"mode":"fixed","currency":"USD","amount":"0.004000"},"protocols":[{"x402":{"scheme":"exact","network":"eip155:8453","currency":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","recipient":"0xb3f4de103F34b99f0Da19B4F16D6B53a14C2194A"}},{"mpp":{"method":"evm","intent":"charge","network":"8453","currency":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","recipient":"0xb3f4de103F34b99f0Da19B4F16D6B53a14C2194A"}},{"mpp":{"method":"tempo","intent":"charge","network":"4217","currency":"0x20c000000000000000000000b9537d11c60e8b50","recipient":"0xb3f4de103F34b99f0Da19B4F16D6B53a14C2194A"}}],"network":"4217","recipient":"0xb3f4de103F34b99f0Da19B4F16D6B53a14C2194A","offers":[{"amount":"4000","currency":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","description":"Count the LLM tokens in text for a given model or encoding — exact for OpenAI and open models (Llama, Mistral, Qwen, Gemma, DeepSeek, Command-R); labelled-approximate for Claude & Gemini.","intent":"charge","method":"evm","recipient":"0xb3f4de103F34b99f0Da19B4F16D6B53a14C2194A"},{"amount":"4000","currency":"0x20c000000000000000000000b9537d11c60e8b50","description":"Count the LLM tokens in text for a given model or encoding — exact for OpenAI and open models (Llama, Mistral, Qwen, Gemma, DeepSeek, Command-R); labelled-approximate for Claude & Gemini.","intent":"charge","method":"tempo","recipient":"0xb3f4de103F34b99f0Da19B4F16D6B53a14C2194A"}]}}}},"x-service-info":{"categories":["compute"],"docs":{"homepage":"https://tokens.openverbs.com","apiReference":"https://tokens.openverbs.com/openapi.json"}}}