Count Tokens (Claude)

curl --request POST \
  --url https://api.mixroute.ai/v1/messages/count_tokens \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "claude-opus-4-8",
    "messages": [
      {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

response = client.messages.count_tokens(
    model="claude-opus-4-8",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)
print(f"Input tokens: {response.input_tokens}")

const response = await fetch('https://api.mixroute.ai/v1/messages/count_tokens', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer sk-xxxxxxxxxx',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'claude-opus-4-8',
    messages: [
      { role: 'user', content: 'Hello, how are you?' }
    ]
  })
});
const data = await response.json();
console.log(data);

<?php
$client = new GuzzleHttp\Client();
$response = $client->post('https://api.mixroute.ai/v1/messages/count_tokens', [
    'headers' => [
        'Authorization' => 'Bearer sk-xxxxxxxxxx',
        'Content-Type' => 'application/json',
    ],
    'json' => [
        'model' => 'claude-opus-4-8',
        'messages' => [
            ['role' => 'user', 'content' => 'Hello, how are you?']
        ]
    ]
]);
echo $response->getBody();

package main

import (
    "bytes"
    "encoding/json"
    "net/http"
)

func main() {
    payload := map[string]interface{}{
        "model": "claude-opus-4-8",
        "messages": []map[string]string{
            {"role": "user", "content": "Hello, how are you?"},
        },
    }
    body, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1/messages/count_tokens", bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
    req.Header.Set("Content-Type", "application/json")
    http.DefaultClient.Do(req)
}

import java.net.http.*;
import java.net.URI;

HttpClient client = HttpClient.newHttpClient();
String json = """
    {
      "model": "claude-opus-4-8",
      "messages": [
        {"role": "user", "content": "Hello, how are you?"}
      ]
    }
    """;
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://api.mixroute.ai/v1/messages/count_tokens"))
    .header("Authorization", "Bearer sk-xxxxxxxxxx")
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString(json))
    .build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

require 'net/http'
require 'json'

uri = URI('https://api.mixroute.ai/v1/messages/count_tokens')
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true

request = Net::HTTP::Post.new(uri)
request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
request['Content-Type'] = 'application/json'
request.body = {
  model: 'claude-opus-4-8',
  messages: [
    { role: 'user', content: 'Hello, how are you?' }
  ]
}.to_json

response = http.request(request)
puts response.body

{
  "input_tokens": 14
}

POST

messages

count_tokens

curl --request POST \
  --url https://api.mixroute.ai/v1/messages/count_tokens \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "claude-opus-4-8",
    "messages": [
      {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

response = client.messages.count_tokens(
    model="claude-opus-4-8",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)
print(f"Input tokens: {response.input_tokens}")

const response = await fetch('https://api.mixroute.ai/v1/messages/count_tokens', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer sk-xxxxxxxxxx',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'claude-opus-4-8',
    messages: [
      { role: 'user', content: 'Hello, how are you?' }
    ]
  })
});
const data = await response.json();
console.log(data);

<?php
$client = new GuzzleHttp\Client();
$response = $client->post('https://api.mixroute.ai/v1/messages/count_tokens', [
    'headers' => [
        'Authorization' => 'Bearer sk-xxxxxxxxxx',
        'Content-Type' => 'application/json',
    ],
    'json' => [
        'model' => 'claude-opus-4-8',
        'messages' => [
            ['role' => 'user', 'content' => 'Hello, how are you?']
        ]
    ]
]);
echo $response->getBody();

package main

import (
    "bytes"
    "encoding/json"
    "net/http"
)

func main() {
    payload := map[string]interface{}{
        "model": "claude-opus-4-8",
        "messages": []map[string]string{
            {"role": "user", "content": "Hello, how are you?"},
        },
    }
    body, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1/messages/count_tokens", bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
    req.Header.Set("Content-Type", "application/json")
    http.DefaultClient.Do(req)
}

import java.net.http.*;
import java.net.URI;

HttpClient client = HttpClient.newHttpClient();
String json = """
    {
      "model": "claude-opus-4-8",
      "messages": [
        {"role": "user", "content": "Hello, how are you?"}
      ]
    }
    """;
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://api.mixroute.ai/v1/messages/count_tokens"))
    .header("Authorization", "Bearer sk-xxxxxxxxxx")
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString(json))
    .build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

require 'net/http'
require 'json'

uri = URI('https://api.mixroute.ai/v1/messages/count_tokens')
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true

request = Net::HTTP::Post.new(uri)
request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
request['Content-Type'] = 'application/json'
request.body = {
  model: 'claude-opus-4-8',
  messages: [
    { role: 'user', content: 'Hello, how are you?' }
  ]
}.to_json

response = http.request(request)
puts response.body

{
  "input_tokens": 14
}

Introduction

Calculate the token count for Claude messages, used for cost estimation before sending requests. This endpoint does not consume quota, only performs local calculation.

Authentication

Bearer Token, e.g., Bearer sk-xxxxxxxxxx

Request Parameters

string

required

Claude model identifier, supported models include:

claude-opus-4-8
claude-sonnet-5
claude-haiku-4-5
Other Claude series models

array

required

Conversation messages list, each element contains role (user/assistant) and content. content can be a string or media content array.Supported content types:

Plain text messages
Multimodal messages (with images)
Tool call results

string

System prompt (optional), can be a string or media content array. Used to set model behavior and role.

array

Tool definition list (optional), used to calculate tool call related token count.

Response Parameters

integer

Total token count of input messages, including:

All messages token count
System prompt token count
Tools definition token count (if any)

Basic Examples

Simple Text Message
With System Prompt
Multi-turn Conversation

curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-opus-4-8",
    "messages": [
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ]
  }'

curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-opus-4-8",
    "system": "You are a helpful AI assistant.",
    "messages": [
      {
        "role": "user",
        "content": "What is artificial intelligence?"
      }
    ]
  }'

curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-opus-4-8",
    "messages": [
      {
        "role": "user",
        "content": "Hello"
      },
      {
        "role": "assistant",
        "content": "Hello! How can I help you?"
      },
      {
        "role": "user",
        "content": "Tell me about the history of artificial intelligence"
      }
    ]
  }'

Python Example

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

# Count tokens
response = client.messages.count_tokens(
    model="claude-opus-4-8",
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ]
)

print(f"Input tokens: {response.input_tokens}")

Response Example

{
  "input_tokens": 14
}

Advanced Use Cases

With Tool Definitions
Multimodal Content

curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-opus-4-8",
    "messages": [
      {
        "role": "user",
        "content": "What is the weather in San Francisco?"
      }
    ],
    "tools": [
      {
        "name": "get_weather",
        "description": "Get the current weather in a given location",
        "input_schema": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state, e.g. San Francisco, CA"
            }
          },
          "required": ["location"]
        }
      }
    ]
  }'

curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-opus-4-8",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What is in this image?"
          },
          {
            "type": "image",
            "source": {
              "type": "url",
              "url": "https://example.com/image.jpg"
            }
          }
        ]
      }
    ]
  }'

Use Cases

1. Cost Estimation

Calculate token count before sending bulk requests to estimate costs:

# Batch cost calculation
messages_batch = [...]  # Batch messages
total_tokens = 0

for messages in messages_batch:
    response = client.messages.count_tokens(
        model="claude-opus-4-8",
        messages=messages
    )
    total_tokens += response.input_tokens

# Calculate total cost based on pricing
cost = total_tokens * price_per_token
print(f"Estimated cost: ${cost:.4f}")

2. Context Window Management

Check if messages exceed the model’s context window limit:

MAX_CONTEXT_WINDOW = 1000000  # Claude Sonnet 5 context window

response = client.messages.count_tokens(
    model="claude-opus-4-8",
    messages=long_conversation
)

if response.input_tokens > MAX_CONTEXT_WINDOW:
    print(f"Warning: Message token count ({response.input_tokens}) exceeds context window limit")
    # Execute message truncation or summarization

3. Prompt Optimization

Compare token consumption of different prompts:

prompts = [
    "Concise prompt...",
    "Detailed prompt...",
    "Very detailed prompt..."
]

for prompt in prompts:
    response = client.messages.count_tokens(
        model="claude-opus-4-8",
        system=prompt,
        messages=[{"role": "user", "content": "Test"}]
    )
    print(f"{len(prompt)} characters -> {response.input_tokens} tokens")

Notes

This endpoint does not make actual AI requests, does not consume quota
Does not include output-related parameters like max_tokens, only calculates input token count
Image tokens use fixed estimates (approx 1000 tokens), actual may vary based on resolution

Error Handling

Missing Required Parameters

{
  "type": "error",
  "error": {
    "type": "invalid_request_error",
    "message": "Key: 'ClaudeCountTokensRequest.Model' Error:Field validation for 'Model' failed on the 'required' tag"
  }
}

Invalid API Key

{
  "error": {
    "message": "Invalid token",
    "type": "invalid_request_error"
  }
}

Pricing - Learn about token billing standards
Model List - View supported Claude models
Create Message Request (Claude) - Send actual Claude requests

curl --request POST \
  --url https://api.mixroute.ai/v1/messages/count_tokens \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "claude-opus-4-8",
    "messages": [
      {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

response = client.messages.count_tokens(
    model="claude-opus-4-8",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)
print(f"Input tokens: {response.input_tokens}")

const response = await fetch('https://api.mixroute.ai/v1/messages/count_tokens', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer sk-xxxxxxxxxx',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'claude-opus-4-8',
    messages: [
      { role: 'user', content: 'Hello, how are you?' }
    ]
  })
});
const data = await response.json();
console.log(data);

<?php
$client = new GuzzleHttp\Client();
$response = $client->post('https://api.mixroute.ai/v1/messages/count_tokens', [
    'headers' => [
        'Authorization' => 'Bearer sk-xxxxxxxxxx',
        'Content-Type' => 'application/json',
    ],
    'json' => [
        'model' => 'claude-opus-4-8',
        'messages' => [
            ['role' => 'user', 'content' => 'Hello, how are you?']
        ]
    ]
]);
echo $response->getBody();

package main

import (
    "bytes"
    "encoding/json"
    "net/http"
)

func main() {
    payload := map[string]interface{}{
        "model": "claude-opus-4-8",
        "messages": []map[string]string{
            {"role": "user", "content": "Hello, how are you?"},
        },
    }
    body, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1/messages/count_tokens", bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
    req.Header.Set("Content-Type", "application/json")
    http.DefaultClient.Do(req)
}

import java.net.http.*;
import java.net.URI;

HttpClient client = HttpClient.newHttpClient();
String json = """
    {
      "model": "claude-opus-4-8",
      "messages": [
        {"role": "user", "content": "Hello, how are you?"}
      ]
    }
    """;
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://api.mixroute.ai/v1/messages/count_tokens"))
    .header("Authorization", "Bearer sk-xxxxxxxxxx")
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString(json))
    .build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

require 'net/http'
require 'json'

uri = URI('https://api.mixroute.ai/v1/messages/count_tokens')
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true

request = Net::HTTP::Post.new(uri)
request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
request['Content-Type'] = 'application/json'
request.body = {
  model: 'claude-opus-4-8',
  messages: [
    { role: 'user', content: 'Hello, how are you?' }
  ]
}.to_json

response = http.request(request)
puts response.body

{
  "input_tokens": 14
}

Create Messages (Claude)Text Embeddings

Popular Models

Smart Routing

OpenAI SDK Usage

Text Series

Embedding Series

Image Series

Video Series

Others

Introduction

Authentication

Request Parameters

Response Parameters

Basic Examples

Python Example

Response Example

Advanced Use Cases

Use Cases

1. Cost Estimation

2. Context Window Management

3. Prompt Optimization

Notes

Error Handling

Missing Required Parameters

Invalid API Key

​Introduction

​Authentication

​Request Parameters

​Response Parameters

​Basic Examples

​Python Example

​Response Example

​Advanced Use Cases

​Use Cases

​1. Cost Estimation

​2. Context Window Management

​3. Prompt Optimization

​Notes

​Error Handling

​Missing Required Parameters

​Invalid API Key

​Related Resources

Introduction

Authentication

Request Parameters

Response Parameters

Basic Examples

Python Example

Response Example

Advanced Use Cases

Use Cases

1. Cost Estimation

2. Context Window Management

3. Prompt Optimization

Notes

Error Handling

Missing Required Parameters

Invalid API Key

Related Resources