Model Comparison

GPT-4.1 nano vs Qwen3 VL 235B A22B ThinkingWhich is better in 2026?

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. GPT-4.1 nano is 6.9x cheaper per token.

Verdict: GPT-4.1 nano vs Qwen3 VL 235B A22B Thinking — which is better?

GPT-4.1 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-4.1 nano outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 4 benchmarks (CharXiv-R, IFEval, MMLU, Multi-IF). Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

On price, GPT-4.1 nano is roughly 6.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GPT-4.1 nano also accepts a larger context window (1,047,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose GPT-4.1 nano if…

  • cost matters — it's about 6.9x cheaper per token
  • you process long inputs — it offers a 1,047,576 token context window

Choose Qwen3 VL 235B A22B Thinking if…

  • you want the strongest raw capability — it leads on 4 of 4 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

4 benchmarks

GPT-4.1 nano outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 4 benchmarks (CharXiv-R, IFEval, MMLU, Multi-IF).

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GPT-4.1 nano costs less

For input processing, GPT-4.1 nano ($0.10/1M tokens) is 4.5x cheaper than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).

For output processing, GPT-4.1 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-4.1 nano.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Jul 21 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input tokens$0.45
Output tokens$3.49
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT-4.1 nano accepts 1,047,576 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-4.1 nano is limited to 32,768 tokens.

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GPT-4.1 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-4.1 nano

Text
Images
Audio
Video

Qwen3 VL 235B A22B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 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.

GPT-4.1 nano

Proprietary

Closed source

Qwen3 VL 235B A22B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.

Qwen3 VL 235B A22B Thinking is 5 months newer than GPT-4.1 nano.

GPT-4.1 nano

Apr 14, 2025

1.3 years ago

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

10 months ago

5mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen3 VL 235B A22B Thinking's cutoff date is not specified.

We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Qwen3 VL 235B A22B Thinking's cutoff date.

GPT-4.1 nano

May 2024

Qwen3 VL 235B A22B Thinking

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Provider Availability

GPT-4.1 nano is available from OpenAI. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.

GPT-4.1 nano

openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

Qwen3 VL 235B A22B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.45/1MOutput Price:Output: $3.49/1M
novita logo
Novita
Input Price:Input: $0.98/1MOutput Price:Output: $3.95/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

OpenAI
Larger context window (1,047,576 tokens)
Less expensive input tokens
Less expensive output tokens
Alibaba Cloud / Qwen Team
Has open weights
Higher CharXiv-R score (66.1% vs 40.5%)
Higher IFEval score (88.2% vs 74.5%)
Higher MMLU score (90.6% vs 80.1%)
Higher Multi-IF score (79.1% vs 57.2%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GPT-4.1 nano and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.

GPT-4.1 nano
✓ Preferred
Qwen3 VL 235B A22B Thinking
Open in Playground
AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking

FAQ

Common questions about GPT-4.1 nano vs Qwen3 VL 235B A22B Thinking.

Which is better, GPT-4.1 nano or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. GPT-4.1 nano is made by OpenAI and Qwen3 VL 235B A22B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-4.1 nano compare to Qwen3 VL 235B A22B Thinking in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Qwen3 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%.

Is GPT-4.1 nano cheaper than Qwen3 VL 235B A22B Thinking?

GPT-4.1 nano is 4.5x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. Qwen3 VL 235B A22B Thinking costs $0.45/M input and $3.49/M output via deepinfra.

What are the context window sizes for GPT-4.1 nano and Qwen3 VL 235B A22B Thinking?

GPT-4.1 nano supports 1.0M tokens and Qwen3 VL 235B A22B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4.1 nano and Qwen3 VL 235B A22B Thinking?

Key differences include context window (1.0M vs 262K), input pricing ($0.10 vs $0.45/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4.1 nano and Qwen3 VL 235B A22B Thinking?

GPT-4.1 nano is developed by OpenAI and Qwen3 VL 235B A22B Thinking is developed by Alibaba Cloud / Qwen Team.

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