Model Comparison

Gemini 2.5 Flash vs Qwen3 VL 32B Thinking

Qwen3 VL 32B Thinking shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini 2.5 Flash outperforms in 1 benchmarks (GPQA), while Qwen3 VL 32B Thinking is better at 2 benchmarks (AIME 2025, SimpleQA).

Qwen3 VL 32B Thinking shows notably better performance in the majority of benchmarks.

Sat May 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 2.5 Flash specifies input context (1,048,576 tokens). Only Gemini 2.5 Flash specifies output context (65,536 tokens).

Gemini 2.5 Flash

Input1,048,576 tokens

Output65,536 tokens

Qwen3 VL 32B Thinking

Input- tokens

Output- tokens

Sat May 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 2.5 Flash and Qwen3 VL 32B Thinking support multimodal inputs.

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

Gemini 2.5 Flash

Text

Images

Audio

Video

Qwen3 VL 32B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Gemini 2.5 Flash 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 2.5 Flash

Proprietary

Closed source

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 2.5 Flash was released on 2025-05-20, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Qwen3 VL 32B Thinking is 4 months newer than Gemini 2.5 Flash.

Gemini 2.5 Flash

May 20, 2025

1.0 years ago

Qwen3 VL 32B Thinking

Sep 22, 2025

8 months ago

4mo newer

Knowledge Cutoff

When training data ends

Gemini 2.5 Flash has a documented knowledge cutoff of 2025-01-31, while Qwen3 VL 32B Thinking's cutoff date is not specified.

We can confirm Gemini 2.5 Flash's training data extends to 2025-01-31, but cannot make a direct comparison without Qwen3 VL 32B Thinking's cutoff date.

Gemini 2.5 Flash

Jan 2025

Qwen3 VL 32B Thinking

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Outputs Comparison

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Key Takeaways

Gemini 2.5 Flash

View details

Google

Larger context window (1,048,576 tokens)

Higher GPQA score (82.8% vs 73.1%)

Qwen3 VL 32B Thinking

View details

Alibaba Cloud / Qwen Team

Has open weights

Higher AIME 2025 score (83.7% vs 72.0%)

Higher SimpleQA score (55.4% vs 26.9%)

Gemini 2.5 Flash

Qwen3 VL 32B Thinking

Compare in Playground

Detailed Comparison

AI Model Comparison Table
Feature	Gemini 2.5 Flash	Qwen3 VL 32B Thinking

FAQ

Common questions about Gemini 2.5 Flash vs Qwen3 VL 32B Thinking.

Which is better, Gemini 2.5 Flash or Qwen3 VL 32B Thinking?

Qwen3 VL 32B Thinking shows notably better performance in the majority of benchmarks. Gemini 2.5 Flash 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 2.5 Flash compare to Qwen3 VL 32B Thinking in benchmarks?

Gemini 2.5 Flash scores Global-MMLU-Lite: 88.4%, AIME 2024: 88.0%, FACTS Grounding: 85.3%, GPQA: 82.8%, MMMU: 79.7%. 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 2.5 Flash and Qwen3 VL 32B Thinking?

Gemini 2.5 Flash supports 1.0M 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 2.5 Flash and Qwen3 VL 32B Thinking?

Key differences include licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.5 Flash and Qwen3 VL 32B Thinking?

Gemini 2.5 Flash is developed by Google and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.