Model Comparison

Gemini 1.0 Pro vs Qwen3 VL 32B ThinkingWhich is better in 2026?

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

Verdict: Gemini 1.0 Pro vs Qwen3 VL 32B Thinking — which is better?

Gemini 1.0 Pro (by Google) and Qwen3 VL 32B Thinking (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Gemini 1.0 Pro outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 2 benchmarks (GPQA, MMLU). Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

Choose Gemini 1.0 Pro if…

  • you want predictable pricing at $0.50/M input and $1.50/M output

Choose Qwen3 VL 32B Thinking if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you want the most recent training data — it shipped Sep 2025
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 1.0 Pro outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 2 benchmarks (GPQA, MMLU).

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

Wed Jun 24 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).

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking
Input- tokens
Output- tokens
Wed Jun 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 32B Thinking supports multimodal inputs, whereas Gemini 1.0 Pro does not.

Qwen3 VL 32B Thinking 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

Qwen3 VL 32B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.0 Pro is licensed under a proprietary license, while Qwen3 VL 32B Thinking 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

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Qwen3 VL 32B Thinking is 20 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.4 years ago

Qwen3 VL 32B Thinking

Sep 22, 2025

9 months ago

1.6yr newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while Qwen3 VL 32B Thinking'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 Qwen3 VL 32B Thinking's cutoff date.

Gemini 1.0 Pro

Feb 2024

Qwen3 VL 32B Thinking

—

Outputs Comparison

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Key Takeaways

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

Qwen3 VL 32B Thinking

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Has open weights
Higher GPQA score (73.1% vs 27.9%)
Higher MMLU score (88.7% vs 71.8%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.0 Pro
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking

FAQ

Common questions about Gemini 1.0 Pro vs Qwen3 VL 32B Thinking.

Which is better, Gemini 1.0 Pro or Qwen3 VL 32B Thinking?

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks. Gemini 1.0 Pro is made by Google and Qwen3 VL 32B Thinking 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 Qwen3 VL 32B Thinking in benchmarks?

Gemini 1.0 Pro scores FLEURS: 93.6%, BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for Gemini 1.0 Pro and Qwen3 VL 32B Thinking?

Gemini 1.0 Pro supports 33K tokens and Qwen3 VL 32B Thinking 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 Qwen3 VL 32B Thinking?

Key differences include multimodal support (no vs yes), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.0 Pro and Qwen3 VL 32B Thinking?

Gemini 1.0 Pro is developed by Google and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.

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