GPT-5 nano vs Qwen3-Next-80B-A3B-Thinking
Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks. GPT-5 nano is 3.5x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5 nano outperforms in 0 benchmarks, while Qwen3-Next-80B-A3B-Thinking is better at 2 benchmarks (AIME 2025, GPQA). Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks.
On price, GPT-5 nano is roughly 3.5x 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.
Based on current benchmark, pricing, and model metadata for 2026.
Choose GPT-5 nano
- cost matters — it's about 3.5x cheaper per token
- you process long inputs — it offers a 400,000 token context window
Choose Qwen3-Next-80B-A3B-Thinking
- 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
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5 nano outperforms in 0 benchmarks, while Qwen3-Next-80B-A3B-Thinking is better at 2 benchmarks (AIME 2025, GPQA).
Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5 nano ($0.05/1M tokens) is 3.0x cheaper than Qwen3-Next-80B-A3B-Thinking ($0.15/1M tokens).
For output processing, GPT-5 nano ($0.40/1M tokens) is 3.8x cheaper than Qwen3-Next-80B-A3B-Thinking ($1.50/1M tokens).
In conclusion, Qwen3-Next-80B-A3B-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-Next-80B-A3B-Thinking's 65,536 tokens. GPT-5 nano can generate longer responses up to 128,000 tokens, while Qwen3-Next-80B-A3B-Thinking is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
GPT-5 nano supports multimodal inputs, whereas Qwen3-Next-80B-A3B-Thinking does not.
GPT-5 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5 nano
Qwen3-Next-80B-A3B-Thinking
License
Usage and distribution terms
GPT-5 nano is licensed under a proprietary license, while Qwen3-Next-80B-A3B-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-Next-80B-A3B-Thinking was released on 2025-09-10.
Qwen3-Next-80B-A3B-Thinking is 1 month newer than GPT-5 nano.
Aug 7, 2025
1.1 years ago
Sep 10, 2025
11 months ago
1mo newerKnowledge Cutoff
When training data ends
GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while Qwen3-Next-80B-A3B-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-Next-80B-A3B-Thinking's cutoff date.
May 2024
—
Provider Availability
GPT-5 nano is available from OpenAI. Qwen3-Next-80B-A3B-Thinking is available from Novita.
GPT-5 nano
Qwen3-Next-80B-A3B-Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 nano and Qwen3-Next-80B-A3B-Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 nano vs Qwen3-Next-80B-A3B-Thinking.