Model Marketplace

Qwen-VL-OCR

Copy success!
Try AIAdd to Compare

Overview

Qwen-VL_OCR is an OCR model trained based on Qwen-VL. It aggregates various image-text recognition, parsing, and processing tasks through a unified model approach, offering powerful image-text recognition capabilities.

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
    600

API Reference

Call API
Copy success!
1234567891011121314151617181920212223242526
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen-vl-ocr",
    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)