Model Comparison

Gemini 1.0 Pro vs Qwen2-VL-72B-Instruct

Qwen2-VL-72B-Instruct significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemini 1.0 Pro outperforms in 0 benchmarks, while Qwen2-VL-72B-Instruct is better at 1 benchmark (EgoSchema).

Qwen2-VL-72B-Instruct significantly outperforms across most benchmarks.

Mon May 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 1.0 Pro specifies input context (32,760 tokens). Only Gemini 1.0 Pro specifies output context (8,192 tokens).

Gemini 1.0 Pro

Input32,760 tokens

Output8,192 tokens

Qwen2-VL-72B-Instruct

Input- tokens

Output- tokens

Mon May 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2-VL-72B-Instruct supports multimodal inputs, whereas Gemini 1.0 Pro does not.

Qwen2-VL-72B-Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.0 Pro

Text

Images

Audio

Video

Qwen2-VL-72B-Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

Gemini 1.0 Pro is licensed under a proprietary license, while Qwen2-VL-72B-Instruct uses tongyi-qianwen.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 1.0 Pro

Proprietary

Closed source

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

Qwen2-VL-72B-Instruct is 7 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.3 years ago

Qwen2-VL-72B-Instruct

Aug 29, 2024

1.7 years ago

6mo newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a knowledge cutoff of 2024-02-01, while Qwen2-VL-72B-Instruct has a cutoff of 2023-06-30.

Gemini 1.0 Pro has more recent training data (up to 2024-02-01), making it potentially better informed about events through that date compared to Qwen2-VL-72B-Instruct (2023-06-30).

Gemini 1.0 Pro

Feb 2024

8 mo newer

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

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Key Takeaways

Gemini 1.0 Pro

View details

Google

Larger context window (32,760 tokens)

Qwen2-VL-72B-Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Has open weights

Higher EgoSchema score (77.9% vs 55.7%)

Detailed Comparison

AI Model Comparison Table
Feature	Gemini 1.0 Pro	Qwen2-VL-72B-Instruct

FAQ

Common questions about Gemini 1.0 Pro vs Qwen2-VL-72B-Instruct.

Which is better, Gemini 1.0 Pro or Qwen2-VL-72B-Instruct?

Qwen2-VL-72B-Instruct significantly outperforms across most benchmarks. Gemini 1.0 Pro is made by Google and Qwen2-VL-72B-Instruct 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 Gemini 1.0 Pro compare to Qwen2-VL-72B-Instruct in benchmarks?

Gemini 1.0 Pro scores BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%, MMMU: 47.9%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench: 86.5%.

What are the context window sizes for Gemini 1.0 Pro and Qwen2-VL-72B-Instruct?

Gemini 1.0 Pro supports 33K tokens and Qwen2-VL-72B-Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 1.0 Pro and Qwen2-VL-72B-Instruct?

Key differences include multimodal support (no vs yes), licensing (Proprietary vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.0 Pro and Qwen2-VL-72B-Instruct?

Gemini 1.0 Pro is developed by Google and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.