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GPT-4o vs Qwen VL Max

Compare GPT-4o and Qwen VL Max side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.

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OpenAIGPT-4o

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

QwenQwen VL Max
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OpenAI

GPT-4o vs Qwen VL Max Comparison Table

Evals updated July 24, 2026Pricing updated July 25, 2026

PropertyGPT-4oQwen VL Max
OrganizationOpenAIQwen
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2024Feb 2025
Context Window128K131K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.50
Output $/1M$10.00
Vision Tasks
CaptioningDemo
Chart Question Answering
Classification
Document Question Answering
Image Tagging
Multi-Label Classification
Object Detection
OCRDemo
Vision Language
Visual Question AnsweringDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision

GPT-4o vs Qwen VL Max: Overview

GPT-4o

GPT-4o (“omni”), released by OpenAI in May 2024, is a multimodal flagship model designed to unify text, image, and audio processing in a single system. Unlike earlier GPT-4 variants, GPT-4o supports real-time speech-to-speech interaction, enabling natural voice conversations alongside text and image reasoning. It features a context window of ~128,000 tokens for text input, with smaller output limits (commonly ~16K tokens), and has a knowledge cutoff of October 2023.

The model is optimized for efficiency and multilingual accessibility, supporting over 50 languages and covering ~97% of the world’s speakers. GPT-4o offers a cost-effective balance of speed and capability. It powers ChatGPT across free and paid tiers, making it widely accessible for applications in conversational AI, real-time translation, multimodal assistants, and global-scale communication tools.

Qwen VL Max

Qwen-VL-Max is a proprietary vision-language model developed by Alibaba’s QwenLM team. Released on February 1, 2025, it is the flagship offering in the Qwen-VL family and sits above the VL-Plus tier in capability.

The model supports text and image inputs and provides a context window of up to 131,072 tokens (with a maximum input size of 129,024 tokens), according to Alibaba Cloud Model Studio. While the parameter count for VL-Max has not been publicly disclosed, the broader Qwen2.5-VL series includes open-weight models scaling up to 72B parameters.

Qwen-VL-Max is optimized for advanced multimodal applications such as document parsing, visual reasoning, multilingual analysis, and structured data extraction. Unlike the open Qwen2.5-VL variants, VL-Max is not available as open weights.