Qwen2.5 VL 7B Instruct vs Qwen3 VL 235B A22B Instruct

Compare Qwen2.5 VL 7B Instruct and Qwen3 VL 235B A22B Instruct side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.

Compare Qwen2.5 VL 7B Instruct vs Qwen3 VL 235B A22B Instruct live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Extract and compare text from images across multiple models.

Open OCR in the full playground
QwenQwen2.5 VL 7B Instruct
Run to compare this model.
QwenQwen3 VL 235B A22B Instruct
Run to compare this model.

Models in this comparison

Qwen2.5 VL 7B Instruct vs Qwen3 VL 235B A22B Instruct: Overview

Qwen2.5 VL 7B Instruct

Qwen2.5-VL-7B-Instruct is a 7-billion parameter vision-language model from Alibaba’s QwenLM team, released on January 26, 2025 under the Apache 2.0 license. It is the instruction-tuned variant of the 7B scale in the Qwen2.5-VL family, designed to process multimodal inputs such as text, images, charts, documents, and video. The model enables structured outputs—including JSON for structured content and bounding boxes for visual localization. Weights are publicly available on Hugging Face and GitHub, making it suitable for both research and applied multimodal use.

Qwen3 VL 235B A22B Instruct

Qwen3 VL 235B A22B Instruct is a flagship multimodal vision-language model developed by Qwen (Alibaba Cloud), designed for instruction-following tasks that combine advanced text generation with visual understanding. It serves as a high-end open-weight model for developers and researchers building multimodal AI systems that require strong reasoning, perception, and long-context capabilities.

The model supports interleaved text and image inputs, very long context windows (up to roughly 256K tokens), and efficient inference through a mixture-of-experts architecture with about 22B active parameters out of 235B total. In today’s landscape, it competes with top-tier proprietary vision-language models while offering the advantages of open weights and flexible deployment. Typical applications include multimodal assistants, document and image analysis, visual reasoning, and large-context instruction-based workflows.

Qwen2.5 VL 7B Instruct vs Qwen3 VL 235B A22B Instruct Comparison Table

PropertyQwen2.5 VL 7B InstructQwen3 VL 235B A22B Instruct
OrganizationQwenQwen
Categoryopenopen
Modalitymultimodalmultimodal
Release DateJan 2025Sep 2025
Context Window33K256K
Parameters7B235B
LicenseApache 2.0Apache 2.0
Pricing per 1M tokens
Input $/1M$0.200
Output $/1M$0.880
Vision Tasks
CaptioningDemoDemo
Object Detection
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
52.24%
Avg Response Time47.64s
Defect Detection
60%(9/15)
Document Understanding
77.8%(7/9)
Object Counting
0%(0/10)
Object Understanding
57.1%(8/14)
Spatial Understanding
57.9%(11/19)