Model Comparison

Gemini 3.1 Pro vs Qwen2.5 VL 72B Instruct

Gemini 3.1 Pro significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemini 3.1 Pro outperforms in 1 benchmarks (MMMU-Pro), while Qwen2.5 VL 72B Instruct is better at 0 benchmarks.

Gemini 3.1 Pro significantly outperforms across most benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Google
Gemini 3.1 Pro
Input tokens$2.50
Output tokens$15.00
Best providerGoogle
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Only Gemini 3.1 Pro specifies input context (1,048,576 tokens). Only Gemini 3.1 Pro specifies output context (65,536 tokens).

Google
Gemini 3.1 Pro
Input1,048,576 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 3.1 Pro and Qwen2.5 VL 72B Instruct support multimodal inputs.

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

Gemini 3.1 Pro

Text
Images
Audio
Video

Qwen2.5 VL 72B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.1 Pro is licensed under a proprietary license, while Qwen2.5 VL 72B Instruct uses tongyi-qianwen.

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

Gemini 3.1 Pro

Proprietary

Closed source

Qwen2.5 VL 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

Gemini 3.1 Pro was released on 2026-02-19, while Qwen2.5 VL 72B Instruct was released on 2025-01-26.

Gemini 3.1 Pro is 13 months newer than Qwen2.5 VL 72B Instruct.

Gemini 3.1 Pro

Feb 19, 2026

1 months ago

1.1yr newer
Qwen2.5 VL 72B Instruct

Jan 26, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while Qwen2.5 VL 72B Instruct's cutoff date is not specified.

We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without Qwen2.5 VL 72B Instruct's cutoff date.

Gemini 3.1 Pro

Jan 2025

Qwen2.5 VL 72B Instruct

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (1,048,576 tokens)
Higher MMMU-Pro score (80.5% vs 51.1%)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 72B Instruct

View details

Alibaba Cloud / Qwen Team

Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 3.1 Pro
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct

FAQ

Common questions about Gemini 3.1 Pro vs Qwen2.5 VL 72B Instruct

Gemini 3.1 Pro significantly outperforms across most benchmarks. Gemini 3.1 Pro is made by Google and Qwen2.5 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.
Gemini 3.1 Pro scores t2-bench: 99.3%, LiveCodeBench Pro: 96.2%, GPQA: 94.3%, MMMLU: 92.6%, BrowseComp: 85.9%. Qwen2.5 VL 72B Instruct scores DocVQA: 96.4%, Android Control Low_EM: 93.7%, ChartQA: 89.5%, OCRBench: 88.5%, AI2D: 88.4%.
Gemini 3.1 Pro supports 1.0M tokens and Qwen2.5 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.
Key differences include licensing (Proprietary vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.
Gemini 3.1 Pro is developed by Google and Qwen2.5 VL 72B Instruct is developed by Alibaba Cloud / Qwen Team.