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Gemini 2.0 Flash Thinking vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash Thinking leads with 3.8% higher average benchmark score. Gemini 2.0 Flash Thinking supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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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Microsoft
Phi 4 Mini Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 68.0% across 3 benchmarks. It excels particularly in MATH-500 (94.6%), AIME (57.5%), GPQA (52.0%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
3 months newer
Gemini 2.0 Flash Thinking
2025-01-21
Phi 4 Mini Reasoning
Microsoft
2025-04-30
Average performance across 5 common benchmarks
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Gemini 2.0 Flash Thinking
Average Score:44.6%(+3.8%)
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Phi 4 Mini Reasoning
Average Score:40.8%
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash Thinking
2024-08-01
Phi 4 Mini Reasoning
2025-02-01
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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Phi 4 Mini Reasoning
0 providers
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Gemini 2.0 Flash Thinking
Avg Score:44.6%(+3.8%)
Providers:0
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Phi 4 Mini Reasoning
Avg Score:40.8%
Providers:0