Model Comparison
GPT-5 nano vs Qwen3 VL 235B A22B ThinkingWhich is better in 2026?
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. GPT-5 nano is 8.8x cheaper per token.
Verdict: GPT-5 nano vs Qwen3 VL 235B A22B Thinking — which is better?
GPT-5 nano (by OpenAI) and Qwen3 VL 235B A22B Thinking (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-5 nano outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (AIME 2025, Humanity's Last Exam). Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
On price, GPT-5 nano is roughly 8.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5 nano also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-5 nano if…
- cost matters — it's about 8.8x cheaper per token
- you process long inputs — it offers a 400,000 token context window
Choose Qwen3 VL 235B A22B Thinking if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5 nano outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (AIME 2025, Humanity's Last Exam).
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5 nano ($0.05/1M tokens) is 9.0x cheaper than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, GPT-5 nano ($0.40/1M tokens) is 8.7x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than GPT-5 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5 nano accepts 400,000 input tokens compared to Qwen3 VL 235B A22B Thinking's 262,144 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while GPT-5 nano is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-5 nano and Qwen3 VL 235B A22B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5 nano
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
GPT-5 nano is licensed under a proprietary license, while Qwen3 VL 235B A22B Thinking 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 nano was released on 2025-08-07, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.
Qwen3 VL 235B A22B Thinking is 2 months newer than GPT-5 nano.
Aug 7, 2025
11 months ago
Sep 22, 2025
10 months ago
1mo newerKnowledge Cutoff
When training data ends
GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while Qwen3 VL 235B A22B Thinking's cutoff date is not specified.
We can confirm GPT-5 nano's training data extends to 2024-05-30, but cannot make a direct comparison without Qwen3 VL 235B A22B Thinking's cutoff date.
May 2024
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Provider Availability
GPT-5 nano is available from OpenAI. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
GPT-5 nano
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Key Takeaways
GPT-5 nano
View detailsOpenAI
Qwen3 VL 235B A22B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-5 nano and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT-5 nano vs Qwen3 VL 235B A22B Thinking.