GPT-5 mini vs Qwen2.5-Coder 32B Instruct
GPT-5 mini leads the LLM Stats Score 27.3 to 2.0. Qwen2.5-Coder 32B Instruct is 7.6x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5 mini leads the overall LLM Stats Score 27.3 to 2.0, ranking #144 overall.
On price, Qwen2.5-Coder 32B Instruct is roughly 7.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5 mini also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5 mini
- overall performance matters — it scores 27.3 and ranks #144 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Aug 2025
Choose Qwen2.5-Coder 32B Instruct
- cost matters — it's about 7.6x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for GPT-5 mini · 15 for Qwen2.5-Coder 32B Instruct
GPT-5 mini and Qwen2.5-Coder 32B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5 mini ($0.25/1M tokens) is 2.8x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, GPT-5 mini ($2.00/1M tokens) is 22.2x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, GPT-5 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
GPT-5 mini accepts 400,000 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5 mini supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
GPT-5 mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5 mini
Qwen2.5-Coder 32B Instruct
License
Usage and distribution terms
GPT-5 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-5 mini was released on 2025-08-07, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
GPT-5 mini is 11 months newer than Qwen2.5-Coder 32B Instruct.
Aug 7, 2025
1.1 years ago
10mo newerSep 19, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
GPT-5 mini has a documented knowledge cutoff of 2024-05-30, while Qwen2.5-Coder 32B Instruct's cutoff date is not specified.
We can confirm GPT-5 mini's training data extends to 2024-05-30, but cannot make a direct comparison without Qwen2.5-Coder 32B Instruct's cutoff date.
May 2024
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Provider Availability
GPT-5 mini is available from OpenAI. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
GPT-5 mini
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 mini and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 mini vs Qwen2.5-Coder 32B Instruct.