---
title: Qwen2.5-VL (72B) Instruct — Multimodal Vision Language ...
description: Generate intelligent responses from images, videos, and documents. Try Qwen2.5-VL (72B) Instruct API for advanced multimodal understanding.
url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/qwen25-vl-72b-instruct
canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/qwen25-vl-72b-instruct
type: website
component: Seo/ModelPage
generated_at: 2026-05-13T10:35:26.984234Z
---

Available now on ModelsLab · Language Model

Qwen2.5-VL (72B) Instruct
Vision. Language. Understanding.
---

[Try Qwen2.5-VL (72B) Instruct](/models/qwen/Qwen-Qwen2.5-VL-72B-Instruct) [API Documentation](https://docs.modelslab.com)

Multimodal Intelligence at Scale
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Visual Reasoning

### Image, Video, Document Understanding

Process images, videos up to 1 hour, and documents with precise visual localization and event detection.

Extended Context

### 32K to 128K Token Window

Handle long-form content and complex queries with native 32K tokens, extendable to 128K using YaRN.

Production Ready

### Fine-Tuning and Customization

Optimize for your domain using LoRA-based fine-tuning on dedicated GPUs for personalized performance.

Examples

See what Qwen2.5-VL (72B) Instruct can create
---

Copy any prompt below and try it yourself in the [playground](/models/qwen/Qwen-Qwen2.5-VL-72B-Instruct).

Document Analysis

“Analyze this invoice image and extract all line items, totals, and payment terms in structured JSON format.”

Video Summarization

“Watch this 30-minute tutorial video and provide a detailed summary with timestamps of key concepts and action items.”

Chart Interpretation

“Examine this quarterly sales chart and identify trends, anomalies, and provide forecasting insights for the next quarter.”

Multi-Image Reasoning

“Compare these three product photos and generate a detailed comparison report highlighting design differences and material quality.”

For Developers

A few lines of code.
Multimodal intelligence. Few 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 ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

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

FAQ

Common questions about Qwen2.5-VL (72B) Instruct
---

[Read the docs ](https://docs.modelslab.com)

### What can Qwen2.5-VL (72B) Instruct model do?

Qwen2.5-VL (72B) Instruct excels at vision-language tasks including image analysis, video comprehension up to 1 hour, document understanding, and visual reasoning. It supports 201 languages and handles complex multimodal queries with high accuracy.

### What is the context window for Qwen2.5-VL (72B) Instruct API?

The default context length is 32,768 tokens, extendable up to 128K tokens using YaRN. Maximum output is 33K tokens per response for comprehensive long-form generation.

### Does Qwen2.5-VL (72B) Instruct support fine-tuning?

Yes. LoRA-based fine-tuning is supported on dedicated GPUs, allowing you to customize the model with your own data for improved domain-specific performance.

### What are the hardware requirements for Qwen2.5-VL (72B) Instruct?

The model runs efficiently on high-performance GPU setups, supporting both 8x NVIDIA L40S and 8x NVIDIA H100 configurations for optimal throughput and latency.

### How many parameters does Qwen2.5-VL (72B) Instruct have?

Qwen2.5-VL (72B) Instruct contains 73.4 billion parameters, making it the largest model in the Qwen2.5-VL series with superior reasoning and understanding capabilities.

### What languages does Qwen2.5-VL (72B) Instruct support?

The model supports 201 languages natively, making it suitable for global applications requiring multilingual document analysis, video understanding, and cross-language reasoning tasks.

Ready to create?
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Start generating with Qwen2.5-VL (72B) Instruct on ModelsLab.

[Try Qwen2.5-VL (72B) Instruct](/models/qwen/Qwen-Qwen2.5-VL-72B-Instruct) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-05-13*