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Gemini 1.5 Pro vs Qwen2-VL-72B-Instruct

Gemini 1.5 Pro and Qwen2-VL-72B-Instruct are closely matched at 12.1 and 14.5 on the LLM Stats Score.

Google · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Gemini 1.5 Pro and Qwen2-VL-72B-Instruct are closely matched on the overall LLM Stats Score at 12.1 and 14.5.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 1.5 Pro

  • you want predictable pricing at $2.50/M input and $10.00/M output

Choose Qwen2-VL-72B-Instruct

  • you want the most recent training data — it shipped Aug 2024
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Gemini 1.5 Pro
Google
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
12.1
#244
14.5
#224
Reasoning
11.9
#237
11.9
#238
Cost, coverage & limits
Benchmark wins
—
—
Input price
$2.50 / M
— / M
Output price
$10.00 / M
— / M
Context window
2,097,152
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemini 1.5 Pro
Qwen2-VL-72B-Instruct
Vision
9.7#123
11.2#112
Multimodal
13.8#96
12.2#104
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for Gemini 1.5 Pro · 15 for Qwen2-VL-72B-Instruct

No common benchmarks found

Gemini 1.5 Pro and Qwen2-VL-72B-Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Gemini 1.5 Pro specifies input context (2,097,152 tokens). Only Gemini 1.5 Pro specifies output context (8,192 tokens).

Google
Gemini 1.5 Pro
Input2,097,152 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Tue Sep 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 1.5 Pro and Qwen2-VL-72B-Instruct support multimodal inputs.

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

Gemini 1.5 Pro

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 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 1.5 Pro

Proprietary

Closed source

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

Gemini 1.5 Pro was released on 2024-05-01, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

Qwen2-VL-72B-Instruct is 4 months newer than Gemini 1.5 Pro.

Gemini 1.5 Pro

May 1, 2024

2.4 years ago

Qwen2-VL-72B-Instruct

Aug 29, 2024

2.0 years ago

4mo newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Pro has a knowledge cutoff of 2023-11-01, while Qwen2-VL-72B-Instruct has a cutoff of 2023-06-30.

Gemini 1.5 Pro has more recent training data (up to 2023-11-01), making it potentially better informed about events through that date compared to Qwen2-VL-72B-Instruct (2023-06-30).

Gemini 1.5 Pro

Nov 2023

5 mo newer
Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 1.5 Pro and Qwen2-VL-72B-Instruct side-by-side, then vote on the output you prefer.

Gemini 1.5 Pro
✓ Preferred
Qwen2-VL-72B-Instruct
Open in Playground

FAQ

Common questions about Gemini 1.5 Pro vs Qwen2-VL-72B-Instruct.

Which is better, Gemini 1.5 Pro or Qwen2-VL-72B-Instruct?

Gemini 1.5 Pro and Qwen2-VL-72B-Instruct are closely matched on the LLM Stats Score at 12.1 and 14.5. Gemini 1.5 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 capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 1.5 Pro compare to Qwen2-VL-72B-Instruct in benchmarks?

Gemini 1.5 Pro scores XSTest: 98.8%, FLEURS: 93.3%, HellaSwag: 93.3%, GSM8k: 90.8%, BIG-Bench Hard: 89.2%. 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 1.5 Pro and Qwen2-VL-72B-Instruct?

Gemini 1.5 Pro supports 2.1M 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 1.5 Pro and Qwen2-VL-72B-Instruct?

Key differences include LLM Stats Score (12.1 vs 14.5), licensing (Proprietary vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.5 Pro and Qwen2-VL-72B-Instruct?

Gemini 1.5 Pro is developed by Google and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.

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