GPT-5.2 vs Qwen3 32B
GPT-5.2 leads the LLM Stats Score 41.3 to 18.4. Qwen3 32B is 37.0x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5.2 leads the overall LLM Stats Score 41.3 to 18.4, ranking #59 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Qwen3 32B is roughly 37.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.2 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-5.2
- overall performance matters — it scores 41.3 and ranks #59 on LLM Stats
- your work emphasizes reasoning and coding — 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 Dec 2025
Choose Qwen3 32B
- cost matters — it's about 37.0x 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
24 reported for GPT-5.2 · 9 for Qwen3 32B
GPT-5.2 outperforms in 1 benchmarks (AIME 2025), while Qwen3 32B is better at 1 benchmark (LiveBench).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.2 ($1.75/1M tokens) is 21.9x more expensive than Qwen3 32B ($0.08/1M tokens).
For output processing, GPT-5.2 ($14.00/1M tokens) is 50.0x more expensive than Qwen3 32B ($0.28/1M tokens).
In conclusion, GPT-5.2 is more expensive than Qwen3 32B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.2 accepts 400,000 input tokens compared to Qwen3 32B's 40,960 tokens. GPT-5.2 can generate longer responses up to 128,000 tokens, while Qwen3 32B is limited to 40,960 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.2 supports multimodal inputs, whereas Qwen3 32B does not.
GPT-5.2 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.2
Qwen3 32B
License
Usage and distribution terms
GPT-5.2 is licensed under a proprietary license, while Qwen3 32B 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-5.2 was released on 2025-12-11, while Qwen3 32B was released on 2025-04-29.
GPT-5.2 is 8 months newer than Qwen3 32B.
Dec 11, 2025
9 months ago
7mo newerApr 29, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
GPT-5.2 has a documented knowledge cutoff of 2025-08-25, while Qwen3 32B's cutoff date is not specified.
We can confirm GPT-5.2's training data extends to 2025-08-25, but cannot make a direct comparison without Qwen3 32B's cutoff date.
Aug 2025
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Provider Availability
GPT-5.2 is available from OpenAI. Qwen3 32B is available from DeepInfra, Novita, Sambanova.
GPT-5.2
Qwen3 32B
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.2 and Qwen3 32B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.2 vs Qwen3 32B.