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Gemini 2.0 Flash Thinking vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Phi 4 Mini leads with 46.7% higher average benchmark score. Gemini 2.0 Flash Thinking supports multimodal inputs. Overall, Phi 4 Mini 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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Microsoft
Phi 4 Mini is a language model developed by Microsoft. It achieves strong performance with an average score of 65.4% across 17 benchmarks. It excels particularly in GSM8k (88.6%), ARC-C (83.7%), BoolQ (81.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
11 days newer
Gemini 2.0 Flash Thinking
2025-01-21
Phi 4 Mini
Microsoft
2025-02-01
Average performance across 19 common benchmarks
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Gemini 2.0 Flash Thinking
Average Score:11.7%
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Phi 4 Mini
Average Score:58.5%(+46.7%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini
2024-06-01
Gemini 2.0 Flash Thinking
2024-08-01
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
0 providers
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Gemini 2.0 Flash Thinking
Avg Score:11.7%
Providers:0
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Phi 4 Mini
Avg Score:58.5%(+46.7%)
Providers:0