Use the Count Tokens API

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Gen AI SDK for Python

Install

pip install --upgrade google-genai

Set environment variables to use the Gen AI SDK with Vertex AI:

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=us-central1
export GOOGLE_GENAI_USE_VERTEXAI=True

from google import genai
from google.genai.types import HttpOptions

client = genai.Client(http_options=HttpOptions(api_version="v1"))
response = client.models.count_tokens(
    model="gemini-2.0-flash-001",
    contents="What's the highest mountain in Africa?",
)
print(response)
# Example output:
# total_tokens=10
# cached_content_token_count=None

REST

To get the token count and the number of billable characters for a prompt by using the Vertex AI API, send a POST request to the publisher model endpoint.

Before using any of the request data, make the following replacements:

• LOCATION: The region to process the request. Available options include the following:

  Click to expand a partial list of available regions

  • us-central1
  • us-west4
  • northamerica-northeast1
  • us-east4
  • us-west1
  • asia-northeast3
  • asia-southeast1
  • asia-northeast1
• PROJECT_ID: Your project ID.
• MODEL_ID: The model ID of the multimodal model that you want to use.
• ROLE: The role in a conversation associated with the content. Specifying a role is required even in singleturn use cases. Acceptable values include the following:
  • USER: Specifies content that's sent by you.
• TEXT: The text instructions to include in the prompt.

HTTP method and URL:

POST https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/publishers/google/models/MODEL_ID:countTokens

Request JSON body:

{
  "contents": [{
    "role": "ROLE",
    "parts": [{
      "text": "TEXT"
    }]
  }]
}

To send your request, choose one of these options:

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/publishers/google/models/MODEL_ID:countTokens"

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/publishers/google/models/MODEL_ID:countTokens" | Select-Object -Expand Content

You should receive a JSON response similar to the following.

{ "totalTokens": 43 }

Console

To get the token count for a prompt by using Vertex AI Studio in the Google Cloud console, perform the following steps:

1. In the Vertex AI section of the Google Cloud console, go to the Vertex AI Studio page.

   Go to Vertex AI Studio

2. Click either Open Freeform or Open Chat.
3. The number of tokens is calculated and displayed as you type in the Prompt pane. It includes the number of tokens in any input files.
4. To see more details, click <count> tokens to open the Prompt tokenizer.
• To view the tokens in the text prompt that are highlighted with different colors marking the boundary of each token ID, click Token ID to text. Media tokens aren't supported.
• To view the token IDs, click Token ID.

  To close the tokenizer tool pane, click X, or click outside of the pane.

Gen AI SDK for Python

Install

pip install --upgrade google-genai

Set environment variables to use the Gen AI SDK with Vertex AI:

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=us-central1
export GOOGLE_GENAI_USE_VERTEXAI=True

from google import genai
from google.genai.types import HttpOptions, Part

client = genai.Client(http_options=HttpOptions(api_version="v1"))

contents = [
    Part.from_uri(
        file_uri="gs://cloud-samples-data/generative-ai/video/pixel8.mp4",
        mime_type="video/mp4",
    ),
    "Provide a description of the video.",
]

response = client.models.count_tokens(
    model="gemini-2.0-flash-001",
    contents=contents,
)
print(response)
# Example output:
# total_tokens=16252 cached_content_token_count=None

REST

To get the token count and the number of billable characters for a prompt by using the Vertex AI API, send a POST request to the publisher model endpoint.

curl
-X POST
-H "Authorization: Bearer $(gcloud auth print-access-token)"
-H "Content-Type: application/json"
https://${REGION}-aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/${REGION}/publishers/google/models/${MODEL_ID}:countTokens -d
$'{ "contents": [{ "role": "user", "parts": [ { "file_data": { "file_uri": "gs://cloud-samples-data/generative-ai/video/pixel8.mp4", "mime_type": "video/mp4" } }, { "text": "'"$TEXT"'" }] }] }' ```