---
title: "Vertex AI OCR"
url: "/docs/providers/vertex_ocr"
canonical_url: "https://docs.litellm.ai/docs/providers/vertex_ocr"
type: "docs"
last_updated: "2026-10-17"
related:
  - "/docs/providers/vertex_batch"
  - "/docs/providers/vertex_ai_agent_engine"
---
# Vertex AI OCR

> Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt


## Overview

| Property | Details |
|-------|-------|
| Description | Vertex AI OCR provides document intelligence capabilities powered by Mistral, enabling text extraction from PDFs and images |
| Provider Route on LiteLLM | `vertex_ai/` |
| Supported Operations | `/ocr` |
| Link to Provider Doc | [Vertex AI ↗](https://cloud.google.com/vertex-ai)

Extract text from documents and images using Vertex AI's OCR models, powered by Mistral.

## Quick Start

### **LiteLLM SDK**

```python showLineNumbers title="SDK Usage"
import litellm
import os

# Set environment variables
os.environ["VERTEXAI_PROJECT"] = "your-project-id"
os.environ["VERTEXAI_LOCATION"] = "us-central1"

# OCR with PDF URL
response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505",
    document={
        "type": "document_url",
        "document_url": "https://example.com/document.pdf"
    }
)

# Access extracted text
for page in response.pages:
    print(page.markdown)
```

### **LiteLLM PROXY**

```yaml showLineNumbers title="proxy_config.yaml"
model_list:
  - model_name: vertex-ocr
    litellm_params:
      model: vertex_ai/mistral-ocr-2505
      vertex_project: os.environ/VERTEXAI_PROJECT
      vertex_location: os.environ/VERTEXAI_LOCATION
      vertex_credentials: path/to/service-account.json  # Optional
    model_info:
      mode: ocr
```

**Start Proxy**
```bash
litellm --config proxy_config.yaml
```

**Call OCR via Proxy**
```bash showLineNumbers title="cURL Request"
curl -X POST http://localhost:4000/ocr \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-api-key" \
  -d '{
    "model": "vertex-ocr",
    "document": {
      "type": "document_url",
      "document_url": "https://arxiv.org/pdf/2201.04234"
    }
  }'
```

## Authentication

Vertex AI OCR supports multiple authentication methods:

### Service Account JSON

```python showLineNumbers title="Service Account Auth"
response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505",
    document={"type": "document_url", "document_url": "https://..."},
    vertex_project="your-project-id",
    vertex_location="us-central1",
    vertex_credentials="path/to/service-account.json"
)
```

### Application Default Credentials

```python showLineNumbers title="Default Credentials"
# Relies on GOOGLE_APPLICATION_CREDENTIALS environment variable
response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505",
    document={"type": "document_url", "document_url": "https://..."},
    vertex_project="your-project-id",
    vertex_location="us-central1"
)
```

## Document Types

Vertex AI OCR supports both PDFs and images.

### PDF Documents

```python showLineNumbers title="PDF OCR"
response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505",
    document={
        "type": "document_url",
        "document_url": "https://example.com/document.pdf"
    },
    vertex_project="your-project-id",
    vertex_location="us-central1"
)
```

### Image Documents

```python showLineNumbers title="Image OCR"
response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505",
    document={
        "type": "image_url",
        "image_url": "https://example.com/image.png"
    },
    vertex_project="your-project-id",
    vertex_location="us-central1"
)
```

### Base64 Encoded Documents

```python showLineNumbers title="Base64 PDF"
import base64

# Read and encode PDF
with open("document.pdf", "rb") as f:
    pdf_base64 = base64.b64encode(f.read()).decode()

response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505", # This doesn't work for deepseek
    document={
        "type": "document_url",
        "document_url": f"data:application/pdf;base64,{pdf_base64}"
    },
    vertex_project="your-project-id",
    vertex_location="us-central1"
)
```

## Supported Parameters

```python showLineNumbers title="All Parameters"
response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505",
    document={                           # Required: Document to process
        "type": "document_url",
        "document_url": "https://..."
    },
    vertex_project="your-project-id",   # Required: GCP project ID
    vertex_location="us-central1",       # Optional: Defaults to us-central1
    vertex_credentials="path/to/key.json", # Optional: Service account key
    include_image_base64=True,           # Optional: Include base64 images
    pages=[0, 1, 2],                     # Optional: Specific pages to process
    image_limit=10                       # Optional: Limit number of images
)
```

## Response Format

```python showLineNumbers title="Response Structure"
# Response has the following structure
response.pages          # List of pages with extracted text
response.model          # Model used
response.object         # "ocr"
response.usage_info     # Token usage information

# Access page content
for page in response.pages:
    print(f"Page {page.index}:")
    print(page.markdown)
```

## Async Support

```python showLineNumbers title="Async Usage"
import litellm

response = await litellm.aocr(
    model="vertex_ai/mistral-ocr-2505",
    document={
        "type": "document_url",
        "document_url": "https://example.com/document.pdf"
    },
    vertex_project="your-project-id",
    vertex_location="us-central1"
)
```

## Cost Tracking

LiteLLM automatically tracks costs for Vertex AI OCR:

- **Cost per page**: $0.0005 (based on $1.50 per 1,000 pages)

```python showLineNumbers title="View Cost"
response = litellm.ocr(
    model="vertex_ai/mistral-ocr-2505",
    document={"type": "document_url", "document_url": "https://..."},
    vertex_project="your-project-id"
)

# Access cost information
print(f"Cost: ${response._hidden_params.get('response_cost', 0)}")
```

## Important Notes

:::info[URL Conversion]
Vertex AI Mistral OCR endpoints don't have internet access. LiteLLM automatically converts public URLs to base64 data URIs before sending requests to Vertex AI.
:::

:::tip[Regional Availability]
Mistral OCR is available in multiple regions. Specify `vertex_location` to use a region closer to your data:
- `us-central1` (default)
- `europe-west1`
- `asia-southeast1`

Deepseek OCR is only available in global region.
:::

## Supported Models

- `mistral-ocr-2505` - Latest Mistral OCR model on Vertex AI
- `deepseek-ocr-maas` - Lates Deepseek OCR model on Vertex AI

Use the Vertex AI provider prefix: `vertex_ai/<model-name>`

## Related pages

- [Vertex Batch APIs](https://docs.litellm.ai/docs/providers/vertex_batch.md)
- [Vertex AI Agent Engine](https://docs.litellm.ai/docs/providers/vertex_ai_agent_engine.md)