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Gemini 2.0 Flash Thinking vs QwQ-32B
Comprehensive side-by-side LLM comparison
QwQ-32B leads with 37.4% higher average benchmark score. Gemini 2.0 Flash Thinking supports multimodal inputs. Overall, QwQ-32B is the stronger choice for coding tasks.
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Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
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Alibaba Cloud / Qwen Team
QwQ-32B is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 74.6% across 7 benchmarks. It excels particularly in MATH-500 (90.6%), IFEval (83.9%), AIME 2024 (79.5%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
1 month newer
Gemini 2.0 Flash Thinking
2025-01-21
QwQ-32B
Alibaba Cloud / Qwen Team
2025-03-05
Average performance across 8 common benchmarks
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Gemini 2.0 Flash Thinking
Average Score:27.9%
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QwQ-32B
Average Score:65.3%(+37.4%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash Thinking
2024-08-01
QwQ-32B
2024-11-28
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.0 Flash Thinking
0 providers
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QwQ-32B
0 providers
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Gemini 2.0 Flash Thinking
Avg Score:27.9%
Providers:0
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QwQ-32B
Avg Score:65.3%(+37.4%)
Providers:0