Model Comparison

Gemini 2.0 Flash vs Qwen2-VL-72B-Instruct

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

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemini 2.0 Flash outperforms in 0 benchmarks, while Qwen2-VL-72B-Instruct is better at 1 benchmark (EgoSchema).

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

Tue May 05 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 2.0 Flash specifies input context (1,048,576 tokens). Only Gemini 2.0 Flash specifies output context (8,192 tokens).

Google
Gemini 2.0 Flash
Input1,048,576 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Tue May 05 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 2.0 Flash and Qwen2-VL-72B-Instruct support multimodal inputs.

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

Gemini 2.0 Flash

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.0 Flash 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 2.0 Flash

Proprietary

Closed source

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

Gemini 2.0 Flash was released on 2024-12-01, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

Gemini 2.0 Flash is 3 months newer than Qwen2-VL-72B-Instruct.

Gemini 2.0 Flash

Dec 1, 2024

1.4 years ago

3mo newer
Qwen2-VL-72B-Instruct

Aug 29, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash has a knowledge cutoff of 2024-08-01, while Qwen2-VL-72B-Instruct has a cutoff of 2023-06-30.

Gemini 2.0 Flash has more recent training data (up to 2024-08-01), making it potentially better informed about events through that date compared to Qwen2-VL-72B-Instruct (2023-06-30).

Gemini 2.0 Flash

Aug 2024

1.2 yr newer
Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (1,048,576 tokens)
Alibaba Cloud / Qwen Team

Qwen2-VL-72B-Instruct

View details

Alibaba Cloud / Qwen Team

Has open weights
Higher EgoSchema score (77.9% vs 71.5%)
GoogleGemini 2.0 Flash
Alibaba Cloud / Qwen TeamQwen2-VL-72B-Instruct

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 2.0 Flash
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct

FAQ

Common questions about Gemini 2.0 Flash vs Qwen2-VL-72B-Instruct.

Which is better, Gemini 2.0 Flash or Qwen2-VL-72B-Instruct?

Qwen2-VL-72B-Instruct significantly outperforms across most benchmarks. Gemini 2.0 Flash 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 2.0 Flash compare to Qwen2-VL-72B-Instruct in benchmarks?

Gemini 2.0 Flash scores Natural2Code: 92.9%, MATH: 89.7%, FACTS Grounding: 83.6%, MMLU-Pro: 76.4%, EgoSchema: 71.5%. 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 2.0 Flash and Qwen2-VL-72B-Instruct?

Gemini 2.0 Flash supports 1.0M 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 2.0 Flash and Qwen2-VL-72B-Instruct?

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

Who makes Gemini 2.0 Flash and Qwen2-VL-72B-Instruct?

Gemini 2.0 Flash is developed by Google and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.