GPT-4o vs Qwen3 VL 235B A22B Thinking
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Qwen3 VL 235B A22B Thinking is 3.6x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-4o outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, MMLU-Pro). Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
On price, Qwen3 VL 235B A22B Thinking is roughly 3.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 235B A22B Thinking also accepts a larger context window (262,144 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-4o
- you want predictable pricing at $2.50/M input and $10.00/M output
Choose Qwen3 VL 235B A22B Thinking
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 3.6x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- 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-4o outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, MMLU-Pro).
Qwen3 VL 235B A22B 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-4o ($2.50/1M tokens) is 5.6x more expensive than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, GPT-4o ($10.00/1M tokens) is 2.9x more expensive than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, GPT-4o is more expensive than Qwen3 VL 235B A22B Thinking.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to GPT-4o's 128,000 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while GPT-4o is limited to 4,096 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-4o and Qwen3 VL 235B A22B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4o
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
GPT-4o 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-4o was released on 2024-05-13, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.
Qwen3 VL 235B A22B Thinking is 17 months newer than GPT-4o.
May 13, 2024
2.3 years ago
Sep 22, 2025
11 months ago
1.4yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT-4o is available from Azure, OpenAI. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
GPT-4o
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4o and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4o vs Qwen3 VL 235B A22B Thinking.