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Available now on ModelsLab · Language Model

Qwen: Qwen2.5 VL 32B InstructVision Meets Reasoning

Process Multimodal Data

Image Analysis

Parse Charts Documents

Handles image-text reasoning, charts, UI, and document understanding with Qwen: Qwen2.5 VL 32B Instruct model.

Video Comprehension

Understand Long Videos

Analyzes videos over 1 hour for event detection using Qwen Qwen2 5 VL 32B Instruct API.

Agentic Tools

Visual Grounding Outputs

Generates bounding boxes, points, JSON for objects in Qwen: Qwen2.5 VL 32B Instruct alternative.

Examples

See what Qwen: Qwen2.5 VL 32B Instruct can create

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

Chart Analysis

Analyze this sales chart image. Extract key trends, totals, and comparisons in structured JSON format.

Invoice Extraction

Extract all fields from this invoice scan: date, items, totals, vendor details in JSON.

Video Events

From this video clip of a city timelapse, detect and describe traffic peaks and weather changes.

UI Navigation

Describe this app screenshot UI. Suggest steps to book a flight using visual elements.

For Developers

A few lines of code.
Multimodal inference. One call.

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
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 Qwen: Qwen2.5 VL 32B Instruct

Read the docs

Ready to create?

Start generating with Qwen: Qwen2.5 VL 32B Instruct on ModelsLab.