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Token Count API
x402
Token Count API is a paid API for AI agents from compute-api-production-245d.up.railway.app, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-11).
Estimates the character count, word count, and token count for a given text string
Price / call$0.001
Success—
StatusUnknown
How this service works
Pure computation endpoints paid per call via x402 ($0.001 USDC on Base).
Output
Returns a JSON object with three integer fields: chars (total character count), words (total word count), and tokens (estimated token count) for the submitted text. The token estimate is model-independent.
Example use cases
Pre-flight LLM prompt sizing
“Before I send this system prompt to GPT, can you count how many tokens it uses so I know if it fits within 4096 tokens? Here's the text: 'You are a helpful assistant specialized in customer support for e-commerce platforms. Always be polite, concise, and escalate unresolved issues to a human agent.'”
Document chunking for RAG pipeline
“I need to split this article into chunks under 512 tokens each — can you count the tokens in this paragraph first so I know how to size the splits? The paragraph is: 'Retrieval-augmented generation is a technique that combines large language models with external knowledge bases to produce more accurate and up-to-date responses.'”
Cost estimation before batch LLM job
“I'm about to run 1000 rows of customer feedback through an LLM and want to estimate the token cost — can you count the tokens in this sample review: 'The product arrived two days late and the packaging was damaged, but the item itself works perfectly and customer service was very responsive.'”
Technical details
Endpoint
POSThttps://compute-api-production-245d.up.railway.app/token-count?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a fast, cheap, model-agnostic token estimate without calling a full LLM API. Ideal for pre-flight checks before expensive LLM calls, document chunking logic, or validating that text fits within a context window. Prefer this over tiktoken or similar libraries when you need a hosted, pay-per-call service that integrates into an automated pipeline via x402 payments on Base.
Side effects
- Missing required 'text' field returns a validation error
- Extremely long texts may time out or hit payload size limits
- Token estimate is model-independent and approximate — may differ slightly from model-specific tokenizers like tiktoken
- Payment failure via x402 prevents the call from being processed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| textrequired | string | |
| model | string | Accepted for compatibility; the estimate is model-independent |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| chars | integer | |
| words | integer | |
| tokens | integer |
Tags
x402
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