Model Comparison

Gemini 1.0 Pro vs Qwen2.5 VL 32B Instruct

Qwen2.5 VL 32B Instruct significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Gemini 1.0 Pro outperforms in 0 benchmarks, while Qwen2.5 VL 32B Instruct is better at 4 benchmarks (GPQA, MATH, MMLU, MMMU).

Qwen2.5 VL 32B Instruct significantly outperforms across most benchmarks.

Fri May 01 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
Fri May 01 2026 • llm-stats.com
Google
Gemini 1.0 Pro
Input tokens$0.50
Output tokens$1.50
Best providerGoogle
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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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).

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
Input- tokens
Output- tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas Gemini 1.0 Pro does not.

Qwen2.5 VL 32B 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

Qwen2.5 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.0 Pro is licensed under a proprietary license, while Qwen2.5 VL 32B Instruct uses Apache 2.0.

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

Gemini 1.0 Pro

Proprietary

Closed source

Qwen2.5 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.

Qwen2.5 VL 32B Instruct is 13 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.2 years ago

Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.2 years ago

1.0yr newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while Qwen2.5 VL 32B Instruct's cutoff date is not specified.

We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without Qwen2.5 VL 32B Instruct's cutoff date.

Gemini 1.0 Pro

Feb 2024

Qwen2.5 VL 32B Instruct

Outputs Comparison

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Key Takeaways

Larger context window (32,760 tokens)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Has open weights
Higher GPQA score (46.0% vs 27.9%)
Higher MATH score (82.2% vs 32.6%)
Higher MMLU score (78.4% vs 71.8%)
Higher MMMU score (70.0% vs 47.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.0 Pro
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct

FAQ

Common questions about Gemini 1.0 Pro vs Qwen2.5 VL 32B Instruct

Qwen2.5 VL 32B Instruct significantly outperforms across most benchmarks. Gemini 1.0 Pro is made by Google and Qwen2.5 VL 32B 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 1.0 Pro scores BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%, MMMU: 47.9%. Qwen2.5 VL 32B Instruct scores DocVQA: 94.8%, Android Control Low_EM: 93.3%, HumanEval: 91.5%, ScreenSpot: 88.5%, MBPP: 84.0%.
Gemini 1.0 Pro supports 33K tokens and Qwen2.5 VL 32B 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 multimodal support (no vs yes), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemini 1.0 Pro is developed by Google and Qwen2.5 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.