Qwen2.5 VL 7B Instruct vs Qwen3 VL 30B A3B Instruct

Compare Qwen2.5 VL 7B Instruct and Qwen3 VL 30B A3B Instruct side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.

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Qwen2.5 VL 7B Instruct vs Qwen3 VL 30B A3B 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 30B A3B Instruct

Qwen3 VL 30B A3B Instruct is an open-weight multimodal large language model developed by Alibaba as part of the Qwen family, built for instruction-following tasks that unify text generation with visual and video understanding. Released around October 2025 under the Apache-2.0 license, it targets efficient, high-fidelity vision-language reasoning across very long contexts.

The model accepts text and image inputs and produces text outputs, with strong performance in OCR, spatial reasoning, long-video understanding, and agentic or GUI-centric visual tasks. It uses a Mixture-of-Experts (A3B) design with ~31.1B total parameters and ~3B active per token, paired with Qwen3-VL’s unified multimodal stack (including Interleaved-MRoPE and DeepStack fusion) to process text, images, and video in a single architecture. OCR support expands to 32 languages, enhancing document workflows. With a native ~262K token context window (extendable further), it stands out today for its balance of scale, efficiency, long-context support, and open accessibility in multimodal systems.

Qwen2.5 VL 7B Instruct vs Qwen3 VL 30B A3B Instruct Comparison Table

PropertyQwen2.5 VL 7B InstructQwen3 VL 30B A3B Instruct
OrganizationQwenQwen
Categoryopenopen
Modalitymultimodalmultimodal
Release DateJan 2025Oct 2025
Context Window33K262K
Parameters7B31B
LicenseApache 2.0Apache 2.0
Pricing per 1M tokens
Input $/1M$0.130
Output $/1M$0.520
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)