Model Comparison

GPT-4.1 nano vs Qwen3-235B-A22B-Thinking-2507Which is better in 2026?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. GPT-4.1 nano is 5.6x cheaper per token.

Verdict: GPT-4.1 nano vs Qwen3-235B-A22B-Thinking-2507 — which is better?

GPT-4.1 nano (by OpenAI) and Qwen3-235B-A22B-Thinking-2507 (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 Qwen3-235B-A22B-Thinking-2507 is better at 5 benchmarks (GPQA, IFEval, Multi-IF, TAU-bench Airline, TAU-bench Retail). Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

On price, GPT-4.1 nano is roughly 5.6x 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 5.6x cheaper per token
  • you process long inputs — it offers a 1,047,576 token context window

Choose Qwen3-235B-A22B-Thinking-2507 if…

  • you want the strongest raw capability — it leads on 5 of 5 shared benchmarks
  • you want the most recent training data — it shipped Jul 2025
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

GPT-4.1 nano outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 5 benchmarks (GPQA, IFEval, Multi-IF, TAU-bench Airline, TAU-bench Retail).

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Mon Jun 15 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 3.0x cheaper than Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens).

For output processing, GPT-4.1 nano ($0.40/1M tokens) is 7.5x cheaper than Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens).

In conclusion, Qwen3-235B-A22B-Thinking-2507 is more expensive than GPT-4.1 nano.*

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

Lowest available price from all providers
Mon Jun 15 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input tokens$0.30
Output tokens$3.00
Best providerFireworks
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 Qwen3-235B-A22B-Thinking-2507's 262,144 tokens. Qwen3-235B-A22B-Thinking-2507 can generate longer responses up to 131,072 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
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Mon Jun 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4.1 nano

Text
Images
Audio
Video

Qwen3-235B-A22B-Thinking-2507

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while Qwen3-235B-A22B-Thinking-2507 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

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

Qwen3-235B-A22B-Thinking-2507 is 3 months newer than GPT-4.1 nano.

GPT-4.1 nano

Apr 14, 2025

1.2 years ago

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

10 months ago

3mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen3-235B-A22B-Thinking-2507'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 Qwen3-235B-A22B-Thinking-2507's cutoff date.

GPT-4.1 nano

May 2024

Qwen3-235B-A22B-Thinking-2507

—

Provider Availability

GPT-4.1 nano is available from OpenAI. Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita.

GPT-4.1 nano

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

Qwen3-235B-A22B-Thinking-2507

fireworks logo
Fireworks
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M
* 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)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Alibaba Cloud / Qwen Team
Has open weights
Higher GPQA score (81.1% vs 50.3%)
Higher IFEval score (87.8% vs 74.5%)
Higher Multi-IF score (80.6% vs 57.2%)
Higher TAU-bench Airline score (46.0% vs 14.0%)
Higher TAU-bench Retail score (67.8% vs 22.6%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507

FAQ

Common questions about GPT-4.1 nano vs Qwen3-235B-A22B-Thinking-2507.

Which is better, GPT-4.1 nano or Qwen3-235B-A22B-Thinking-2507?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. GPT-4.1 nano is made by OpenAI and Qwen3-235B-A22B-Thinking-2507 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 Qwen3-235B-A22B-Thinking-2507 in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.

Is GPT-4.1 nano cheaper than Qwen3-235B-A22B-Thinking-2507?

GPT-4.1 nano is 3.0x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. Qwen3-235B-A22B-Thinking-2507 costs $0.30/M input and $3.00/M output via fireworks.

What are the context window sizes for GPT-4.1 nano and Qwen3-235B-A22B-Thinking-2507?

GPT-4.1 nano supports 1.0M tokens and Qwen3-235B-A22B-Thinking-2507 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 Qwen3-235B-A22B-Thinking-2507?

Key differences include context window (1.0M vs 262K), input pricing ($0.10 vs $0.30/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4.1 nano and Qwen3-235B-A22B-Thinking-2507?

GPT-4.1 nano is developed by OpenAI and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.

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