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AgentUtility Token Count Estimator
x402
AgentUtility Token Count Estimator is a paid API for AI agents from x402.agentutility.ai, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).
Estimates token count for a given text and target LLM (GPT-4, Claude, Gemini) using a local heuristic based on cl100k_base/o200k_base tokenizers with model-calibrated multipliers — no upstream API call.
Price / call$0.005
Success—
StatusUnknown
How this service works
Token count / tokenizer estimate / GPT-4 token count / Claude token count / Gemini token count / context-window pre-flight. Pure-local heuristic estimator targeting cl100k_base / o200k_base (GPT-4o) with calibrated multipliers for Claude and Gemini. Input model name is matched against an internal table of supported tokenizers. Accuracy ±5% versus tiktoken on typical English. No upstream call.
Output
Returns a numeric token count estimate for the provided text under the specified model's tokenizer, along with the resolved tokenizer name and an accuracy disclaimer of approximately ±5% versus tiktoken on typical English text. No external API call is made — result is computed locally.
Example use cases
Pre-flight context window check
“Before I send this 10,000-word document to Claude, can you estimate how many tokens it is so I know if it'll fit in a 100k context window?”
LLM cost budgeting for GPT-4o
“I'm about to run a batch of prompts through GPT-4o and want to estimate the total token count for this sample text so I can project my costs — can you count the tokens?”
Multi-model token comparison
“I have this prompt text and I want to know how the token count compares between GPT-4o and Gemini — can you estimate tokens for both models?”
Technical details
Endpoint
POSThttps://x402.agentutility.ai/token-countWhen to prefer
Choose this endpoint when you need a fast, cheap, offline token estimate before committing to an LLM API call — especially useful for context-window pre-flight checks, cost budgeting, or batch processing where calling tiktoken or a live tokenizer API is not feasible. Prefer over live tokenizer APIs when latency or cost of upstream calls matters. Best for English text targeting GPT-4, GPT-4o, Claude, or Gemini.
Side effects
- Unsupported model name returns an error or falls back to default tokenizer
- Very short or empty text may produce zero or near-zero counts
- Non-English or code-heavy text may exceed the ±5% accuracy bound
- Malformed request body returns a 400 error
- Payment not settled via x402 returns a 402 Payment Required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"model": "gpt-4o",
"source": "DIY heuristic (cl100k_base-shaped)",
"text_chars": 46,
"accuracy_note": "Heuristic estimate, ±5% vs tiktoken cl100k_base on typical English text. Larger error on heavy punctuation, code, or non-Latin scripts. Computed locally in-process — instant response.",
"estimated_tokens": 11,
"matched_tokenizer": "gpt-4o"
}
}Tags
x402
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