Model Comparison
GPT-4o mini vs Qwen2.5-Coder 32B InstructWhich is better in 2026?
GPT-4o mini shows notably better performance in the majority of benchmarks. Qwen2.5-Coder 32B Instruct is 2.9x cheaper per token.
Verdict: GPT-4o mini vs Qwen2.5-Coder 32B Instruct — which is better?
GPT-4o mini (by OpenAI) and Qwen2.5-Coder 32B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GPT-4o mini outperforms in 2 benchmarks (MATH, MMLU), while Qwen2.5-Coder 32B Instruct is better at 1 benchmark (HumanEval). GPT-4o mini shows notably better performance in the majority of benchmarks.
On price, Qwen2.5-Coder 32B Instruct is roughly 2.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose GPT-4o mini if…
- you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
Choose Qwen2.5-Coder 32B Instruct if…
- cost matters — it's about 2.9x cheaper per token
- you want the most recent training data — it shipped Sep 2024
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-4o mini outperforms in 2 benchmarks (MATH, MMLU), while Qwen2.5-Coder 32B Instruct is better at 1 benchmark (HumanEval).
GPT-4o mini shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4o mini ($0.15/1M tokens) is 1.7x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, GPT-4o mini ($0.60/1M tokens) is 6.7x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, GPT-4o mini is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Qwen2.5-Coder 32B Instruct can generate longer responses up to 128,000 tokens, while GPT-4o mini is limited to 16,384 tokens.
Input Capabilities
Supported data types and modalities
GPT-4o mini supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
GPT-4o mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4o mini
Qwen2.5-Coder 32B Instruct
License
Usage and distribution terms
GPT-4o mini is licensed under a proprietary license, while Qwen2.5-Coder 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-4o mini was released on 2024-07-18, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Qwen2.5-Coder 32B Instruct is 2 months newer than GPT-4o mini.
Jul 18, 2024
2.0 years ago
Sep 19, 2024
1.8 years ago
2mo newerKnowledge Cutoff
When training data ends
GPT-4o mini has a documented knowledge cutoff of 2023-10-01, while Qwen2.5-Coder 32B Instruct's cutoff date is not specified.
We can confirm GPT-4o mini's training data extends to 2023-10-01, but cannot make a direct comparison without Qwen2.5-Coder 32B Instruct's cutoff date.
Oct 2023
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Provider Availability
GPT-4o mini is available from Azure. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
GPT-4o mini
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Key Takeaways
GPT-4o mini
View detailsOpenAI
Qwen2.5-Coder 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-4o mini and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT-4o mini vs Qwen2.5-Coder 32B Instruct.