Free tool · #2
LLM Token Counter
Count the tokens in any prompt — exact for OpenAI models, estimated for Claude and Gemini.
Prices verified 15 Jul 2026 · 131 models
Token count
29tokens
exacttiktoken o200k_base
≈ $0.000073 to send as input · openai · gpt-4o
- Context window
- 128K in · 16.4K out
- Tokenizer
- openai_tiktoken
- characters
- 131
- words
- 22
- tokens / word
- 1.32
Token map — how o200k_base splits your text
Input cost at scale — this prompt on gpt-4o
| Volume | Tokens | Input cost |
|---|---|---|
| 1 call | 29 | $0.000073 |
| 1K calls | 29,000 | $0.07 |
| 100K calls | 2,900,000 | $7.25 |
| 1M calls | 29,000,000 | $72.50 |
This prompt priced across every model — cheapest first
| Cohere | command-r7b-12-2024 | ~33 | $0.04 | $0.0000012 |
| Azure | ministral-3b | ~33 | $0.04 | $0.0000013 |
| DeepInfra | Qwen2.5-7B-Instruct | ~33 | $0.04 | $0.0000013 |
| OpenAI | gpt-5-nano | 29 | $0.05 | $0.0000014 |
| DeepInfra | Mistral-Small-24B-Instruct-2501 | ~33 | $0.05 | $0.0000016 |
| DeepInfra | phi-4 | ~33 | $0.07 | $0.0000023 |
| gemini-2.0-flash-lite | ~33 | $0.08 | $0.0000025 | |
| OpenAI | gpt-4.1-nano | 29 | $0.10 | $0.0000029 |
| AWS Bedrock | voxtral-small-24b-2507 | ~33 | $0.10 | $0.0000033 |
| gemini-2.0-flash | ~33 | $0.10 | $0.0000033 | |
| gemini-2.5-flash-lite | ~33 | $0.10 | $0.0000033 | |
| Mistral | mistral-small | ~33 | $0.10 | $0.0000033 |
| OpenRouter | ministral-3b-2512 | ~33 | $0.10 | $0.0000033 |
| OpenRouter | mistral-small-3.2-24b-instruct | ~33 | $0.10 | $0.0000033 |
| OpenRouter | ui-tars-1.5-7b | ~33 | $0.10 | $0.0000033 |
| Vercel AI Gateway | llama-4-scout | ~33 | $0.10 | $0.0000033 |
| OpenAI | gpt-4o-mini | 29 | $0.15 | $0.0000043 |
| OpenAI | gpt-4o-mini-search-preview | 29 | $0.15 | $0.0000043 |
| DeepSeek | deepseek-v4-flash | ~33 | $0.14 | $0.0000046 |
| Azure | mistral-nemo | ~33 | $0.15 | $0.0000050 |
| Cohere | command-r-08-2024 | ~33 | $0.15 | $0.0000050 |
| Mistral | ministral-8b-2512 | ~33 | $0.15 | $0.0000050 |
| Vercel AI Gateway | pixtral-12b | ~33 | $0.15 | $0.0000050 |
| OpenAI | gpt-5.4-nano | 29 | $0.20 | $0.0000058 |
| DeepInfra | Llama-Guard-4-12B | ~33 | $0.18 | $0.0000059 |
Use this tool from code — or hand it to your agentagent prompt · REST · MCP
Hand this tool to your coding agent
Paste into Claude Code, Cursor, Codex, or any agent. It learns to call this tool over REST or MCP, reaches for it when you ask, and keeps our sourced/pending labels honest.
You can use telemeter.ai's free "LLM Token Counter" — a keyless, read-only tool (no signup), available as an HTTP API and an MCP tool. What it does: Count the tokens in any prompt — exact for OpenAI models, estimated for Claude and Gemini.
Whenever I ask you something this tool answers, call it and use its result instead of estimating yourself.
REST:
curl -sX POST https://telemeter.ai/api/tools/llm-token-counter -H 'content-type: application/json' -d '{"text":"Summarize the following support ticket in one sentence.","model":"gpt-4o"}'
MCP: the telemeter MCP server at https://telemeter.ai/mcp exposes this as the tool "llm-token-counter" — call it with tools/call.
The response is JSON: { status, data, summary, provenance }. "provenance" carries the source and the date the figure was verified. If status is "pending" or "stale", tell me the value isn't currently verified rather than presenting it as fact.Or call it directly. This tool runs behind one handler with three front doors — this page, a REST endpoint, and an MCP tool. Same result, read-only, no key. The example below is a request that works.
curl -sX POST https://telemeter.ai/api/tools/llm-token-counter \
-H 'content-type: application/json' \
-d '{"text":"Summarize the following support ticket in one sentence.","model":"gpt-4o"}'curl -sX POST https://telemeter.ai/mcp \
-H 'content-type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"llm-token-counter","arguments":{"text":"Summarize the following support ticket in one sentence.","model":"gpt-4o"}}}'{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"type": "object",
"properties": {
"text": {
"type": "string",
"maxLength": 600000
},
"model": {
"type": "string",
"minLength": 1
}
},
"required": [
"text",
"model"
],
"additionalProperties": false
}Want this across your whole stack?
Telemeter tracks real cost, latency, and quality on every production agent run — on the same verified pricing behind this tool.
https://telemeter.ai/tools/llm-token-counterNo account, no cookies, nothing stored — every answer is computed from a sourced registry and never logged. Data notice →