Model Comparison

Qwen2-VL-72B-Instruct vs Qwen3 VL 235B A22B ThinkingWhich is better in 2026?

Qwen3 VL 235B A22B Thinking shows notably better performance in the majority of benchmarks.

Verdict: Qwen2-VL-72B-Instruct vs Qwen3 VL 235B A22B Thinking — which is better?

Qwen2-VL-72B-Instruct (by Alibaba Cloud / Qwen Team) 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.

Qwen2-VL-72B-Instruct outperforms in 1 benchmarks (OCRBench), while Qwen3 VL 235B A22B Thinking is better at 5 benchmarks (InfoVQAtest, MathVista-Mini, MMMU-Pro, MMMUval, RealWorldQA). Qwen3 VL 235B A22B Thinking shows notably better performance in the majority of benchmarks.

Choose Qwen2-VL-72B-Instruct if…

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

Choose Qwen3 VL 235B A22B Thinking if…

  • you want the strongest raw capability — it leads on 6 of 7 shared benchmarks
  • you want the most recent training data — it shipped Sep 2025
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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Qwen2-VL-72B-Instruct outperforms in 1 benchmarks (OCRBench), while Qwen3 VL 235B A22B Thinking is better at 5 benchmarks (InfoVQAtest, MathVista-Mini, MMMU-Pro, MMMUval, RealWorldQA).

Qwen3 VL 235B A22B Thinking shows notably better performance in the majority of benchmarks.

Mon Jun 08 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

162.6B diff

Qwen3 VL 235B A22B Thinking has 162.6B more parameters than Qwen2-VL-72B-Instruct, making it 221.5% larger.

Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
73.4Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
236.0Bparameters
73.4B
Qwen2-VL-72B-Instruct
236.0B
Qwen3 VL 235B A22B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 235B A22B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Thinking specifies output context (262,144 tokens).

Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Mon Jun 08 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen2-VL-72B-Instruct and Qwen3 VL 235B A22B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

Qwen3 VL 235B A22B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen2-VL-72B-Instruct is licensed under tongyi-qianwen, 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.

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Qwen3 VL 235B A22B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen2-VL-72B-Instruct was released on 2024-08-29, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.

Qwen3 VL 235B A22B Thinking is 13 months newer than Qwen2-VL-72B-Instruct.

Qwen2-VL-72B-Instruct

Aug 29, 2024

1.8 years ago

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

8 months ago

1.1yr newer

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while Qwen3 VL 235B A22B Thinking's cutoff date is not specified.

We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without Qwen3 VL 235B A22B Thinking's cutoff date.

Qwen2-VL-72B-Instruct

Jun 2023

Qwen3 VL 235B A22B Thinking

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Outputs Comparison

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Key Takeaways

Alibaba Cloud / Qwen Team

Qwen2-VL-72B-Instruct

View details

Alibaba Cloud / Qwen Team

Higher OCRBench score (87.7% vs 87.5%)
Alibaba Cloud / Qwen Team
Larger context window (262,144 tokens)
Higher InfoVQAtest score (89.5% vs 84.5%)
Higher MathVista-Mini score (85.8% vs 70.5%)
Higher MMMU-Pro score (69.3% vs 46.2%)
Higher MMMUval score (80.6% vs 64.5%)
Higher RealWorldQA score (81.3% vs 77.8%)

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking

FAQ

Common questions about Qwen2-VL-72B-Instruct vs Qwen3 VL 235B A22B Thinking.

Which is better, Qwen2-VL-72B-Instruct or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking shows notably better performance in the majority of benchmarks. Qwen2-VL-72B-Instruct is made by Alibaba Cloud / Qwen Team 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 Qwen2-VL-72B-Instruct compare to Qwen3 VL 235B A22B Thinking in benchmarks?

Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench: 86.5%. Qwen3 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%.

What are the context window sizes for Qwen2-VL-72B-Instruct and Qwen3 VL 235B A22B Thinking?

Qwen2-VL-72B-Instruct supports an unknown number of 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 Qwen2-VL-72B-Instruct and Qwen3 VL 235B A22B Thinking?

Key differences include licensing (tongyi-qianwen vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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