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Gemini 2.0 Flash Thinking vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-vision-instruct leads with 35.6% higher average benchmark score. Overall, Phi-3.5-vision-instruct 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-3.5-vision-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 68.3% across 9 benchmarks. It excels particularly in ScienceQA (91.3%), POPE (86.1%), MMBench (81.9%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
5 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
Gemini 2.0 Flash Thinking
2025-01-21
Average performance across 11 common benchmarks
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Gemini 2.0 Flash Thinking
Average Score:20.3%
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Phi-3.5-vision-instruct
Average Score:55.9%(+35.6%)
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Knowledge Cutoff
Training data recency comparison
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-3.5-vision-instruct
0 providers
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Gemini 2.0 Flash Thinking
Avg Score:20.3%
Providers:0
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Phi-3.5-vision-instruct
Avg Score:55.9%(+35.6%)
Providers:0