GPT-6 Sol vs Qwen3 VL 235B A22B Thinking
GPT-6 Sol leads the LLM Stats Score 49.4 to 26.7. Qwen3 VL 235B A22B Thinking is 3.3x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-6 Sol leads the overall LLM Stats Score 49.4 to 26.7, ranking #21 overall.
On price, Qwen3 VL 235B A22B Thinking is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Sol also accepts a larger context window (1,050,000 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-6 Sol
- overall performance matters — it scores 49.4 and ranks #21 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Qwen3 VL 235B A22B Thinking
- cost matters — it's about 3.3x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
5 reported for GPT-6 Sol · 67 for Qwen3 VL 235B A22B Thinking
GPT-6 Sol and Qwen3 VL 235B A22B Thinkingdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Sol ($2.00/1M tokens) is 4.4x more expensive than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, GPT-6 Sol ($10.00/1M tokens) is 2.9x more expensive than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, GPT-6 Sol 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
GPT-6 Sol accepts 1,050,000 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-6 Sol is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-6 Sol and Qwen3 VL 235B A22B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6 Sol
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
GPT-6 Sol 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-6 Sol was released on 2026-09-22, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.
GPT-6 Sol is 12 months newer than Qwen3 VL 235B A22B Thinking.
Sep 22, 2026
0 days ago
1.0yr newerSep 22, 2025
1.0 years ago
Knowledge Cutoff
When training data ends
GPT-6 Sol has a documented knowledge cutoff of 2026-04-20, while Qwen3 VL 235B A22B Thinking's cutoff date is not specified.
We can confirm GPT-6 Sol's training data extends to 2026-04-20, but cannot make a direct comparison without Qwen3 VL 235B A22B Thinking's cutoff date.
Apr 2026
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Provider Availability
GPT-6 Sol is available from OpenAI. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
GPT-6 Sol
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Sol and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Sol vs Qwen3 VL 235B A22B Thinking.