Model Comparison
GPT-4 Turbo vs Qwen2.5 VL 32B Instruct
Both models are evenly matched across the benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
GPT-4 Turbo outperforms in 2 benchmarks (GPQA, MMLU), while Qwen2.5 VL 32B Instruct is better at 2 benchmarks (HumanEval, MATH).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Context Window
Maximum input and output token capacity
Only GPT-4 Turbo specifies input context (128,000 tokens). Only GPT-4 Turbo specifies output context (4,096 tokens).
Input Capabilities
Supported data types and modalities
Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas GPT-4 Turbo does not.
Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4 Turbo
Qwen2.5 VL 32B Instruct
License
Usage and distribution terms
GPT-4 Turbo is licensed under a proprietary license, while Qwen2.5 VL 32B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-4 Turbo was released on 2024-04-09, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.
Qwen2.5 VL 32B Instruct is 11 months newer than GPT-4 Turbo.
Apr 9, 2024
2.1 years ago
Feb 28, 2025
1.2 years ago
10mo newerKnowledge Cutoff
When training data ends
GPT-4 Turbo has a documented knowledge cutoff of 2023-12-31, while Qwen2.5 VL 32B Instruct's cutoff date is not specified.
We can confirm GPT-4 Turbo's training data extends to 2023-12-31, but cannot make a direct comparison without Qwen2.5 VL 32B Instruct's cutoff date.
Dec 2023
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Outputs Comparison
Key Takeaways
GPT-4 Turbo
View detailsOpenAI
Qwen2.5 VL 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about GPT-4 Turbo vs Qwen2.5 VL 32B Instruct.