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Available now on ModelsLab · Language Model

Qwen2-VL (72B) InstructVision, Video, Reasoning

Try Qwen2-VL (72B) InstructAPI Documentation

See, Understand, Reason Better

Extended Context

Process 20+ Minute Videos

Handle long-form video content for QA, dialogue, and analysis without truncation.

Dynamic Resolution

Arbitrary Image Resolutions

Process images at any resolution with adaptive token mapping for optimal efficiency.

Multilingual Support

Global Text Recognition

Extract and understand text in 30+ languages, including European, Asian, and Arabic scripts.

Examples

See what Qwen2-VL (72B) Instruct can create

Copy any prompt below and try it yourself in the playground.

Document Analysis

“Analyze this architectural blueprint and extract all dimensions, materials, and structural specifications. Format the output as structured JSON with categories for walls, openings, and load-bearing elements.”

Video Event Detection

“Review this 15-minute surveillance footage and identify all significant events. For each event, provide timestamp, description, and confidence level. Output as a timeline with bounding box coordinates.”

Chart Data Extraction

“Extract all data from this financial chart including axis labels, data points, and trends. Return as CSV format with column headers and numerical values.”

Visual Localization

“Locate all product packaging in this retail shelf image. For each item, provide bounding box coordinates, product name, and shelf position (top, middle, bottom).”

For Developers

A few lines of code.
Multimodal reasoning. Three lines.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Qwen2-VL (72B) Instruct

Read the docs

Qwen2-VL handles arbitrary image resolutions and videos over 20 minutes using dynamic token mapping and M-ROPE positional embeddings. It achieves performance on visual benchmarks like MathVista and DocVQA while supporting 30+ languages.

Yes, it processes videos up to 20+ minutes for high-quality video-based question answering, event detection, and content creation. It includes temporal reasoning capabilities for understanding sequences and changes over time.

Yes, it's available through multiple providers with 32.8k token context length and optimized for instruction following, reasoning, and tool usage. Check provider documentation for SLA and rate limit details.

Beyond English and Chinese, it supports most European languages, Japanese, Korean, Arabic, Vietnamese, and other scripts. It can recognize and understand multilingual text within images.

Yes, Qwen2-VL can integrate with mobile phones, robots, and other devices for automatic operation based on visual environment and text instructions, combining complex reasoning with decision-making capabilities.

Ready to create?

Start generating with Qwen2-VL (72B) Instruct on ModelsLab.

Try Qwen2-VL (72B) InstructAPI Documentation