Model Marketplace

Qwen-VL-OCR

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Overview

This model is a snapshot version from November 20, 2025, and is based on the latest Qwen-VL3 architecture with a comprehensive upgrade. It features significant improvements in document parsing and text localization capabilities, as well as substantial reductions in end-to-end latency and illusions.

Input

TextImage

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

  • Input
    $0.07Per 1M tokens
  • Output
    $0.16Per 1M tokens

Rate Limits & Context

  • Max Input
    30K
  • Max Output
    8K
  • Context
    38K
  • TPMTokens Per Minute
    6M
  • RPMRequests Per Minute
    1K

API Reference

Call API
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import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://ap-southeast-1.maas.qwencloudapi.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen-vl-ocr-2025-11-20",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg"
                    },
                },
                {"type": "text", "text": "Output the text in the image only."},
            ],
        },
    ],
)
print(completion.choices[0].message.content)