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GPT-4o mini vs Qwen2.5 VL 7B Instruct

Compare GPT-4o mini and Qwen2.5 VL 7B Instruct side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.

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OpenAIGPT-4o mini

GPT-4o mini is deprecated and can no longer be run. Details and evals are still available on its model page.

QwenQwen2.5 VL 7B Instruct
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GPT-4o mini vs Qwen2.5 VL 7B Instruct: Overview

GPT-4o mini

GPT-4o mini, launched by OpenAI in July 2024, is a lightweight, cost-efficient variant of GPT-4o designed for developers who need strong multimodal reasoning at scale. It supports text and vision inputs (with audio/video support planned) and offers a 128,000-token input context window with outputs up to ~16,000 tokens. Like GPT-4o, it has a knowledge cutoff of October 2023 and integrates the same safety mitigations against misuse and prompt attacks.

GPT-4o mini is significantly cheaper than full GPT-4o while outperforming older models such as GPT-3.5 Turbo. It achieves around 82% on MMLU, reflecting solid reasoning, math, and coding capabilities despite its efficiency focus. The model replaced GPT-3.5 Turbo as the default in ChatGPT for many users, making it widely accessible for everyday conversational AI, educational tools, content generation, and scalable multimodal applications where affordability and speed are priorities.

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.

GPT-4o mini vs Qwen2.5 VL 7B Instruct Comparison Table

PropertyGPT-4o miniQwen2.5 VL 7B Instruct
OrganizationOpenAIQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJul 2024Jan 2025
Context Window128K33K
Parameters7B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$0.150
Output $/1M$0.600
Vision Tasks
CaptioningDemo
Object Detection
OCRDemo
Vision Language
Visual Question AnsweringDemo
Classification
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation 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)