GPT-5 vs Qwen3 VL 4B Thinking
GPT-5 significantly outperforms across most benchmarks. Qwen3 VL 4B Thinking is 10.6x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5 outperforms in 7 benchmarks (AIME 2025, CharXiv-R, ERQA, GPQA, MMLU, MMMU-Pro, VideoMMMU), while Qwen3 VL 4B Thinking is better at 0 benchmarks. GPT-5 significantly outperforms across most benchmarks.
On price, Qwen3 VL 4B Thinking is roughly 10.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5 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
- you want the strongest raw capability — it leads on 7 of 7 shared benchmarks
- you process long inputs — it offers a 400,000 token context window
Choose Qwen3 VL 4B Thinking
- cost matters — it's about 10.6x cheaper per token
- 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 outperforms in 7 benchmarks (AIME 2025, CharXiv-R, ERQA, GPQA, MMLU, MMMU-Pro, VideoMMMU), while Qwen3 VL 4B Thinking is better at 0 benchmarks.
GPT-5 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 ($1.25/1M tokens) is 12.5x more expensive than Qwen3 VL 4B Thinking ($0.10/1M tokens).
For output processing, GPT-5 ($10.00/1M tokens) is 10.0x more expensive than Qwen3 VL 4B Thinking ($1.00/1M tokens).
In conclusion, GPT-5 is more expensive than Qwen3 VL 4B Thinking.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5 accepts 400,000 input tokens compared to Qwen3 VL 4B Thinking's 262,144 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while GPT-5 is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-5 and Qwen3 VL 4B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5
Qwen3 VL 4B Thinking
License
Usage and distribution terms
GPT-5 is licensed under a proprietary license, while Qwen3 VL 4B 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 was released on 2025-08-07, while Qwen3 VL 4B Thinking was released on 2025-09-22.
Qwen3 VL 4B Thinking is 2 months newer than GPT-5.
Aug 7, 2025
1.0 years ago
Sep 22, 2025
11 months ago
1mo newerKnowledge Cutoff
When training data ends
GPT-5 has a documented knowledge cutoff of 2024-09-30, while Qwen3 VL 4B Thinking's cutoff date is not specified.
We can confirm GPT-5's training data extends to 2024-09-30, but cannot make a direct comparison without Qwen3 VL 4B Thinking's cutoff date.
Sep 2024
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Provider Availability
GPT-5 is available from OpenAI. Qwen3 VL 4B Thinking is available from DeepInfra.
GPT-5
Qwen3 VL 4B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 vs Qwen3 VL 4B Thinking.