Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 2.0 Flash Thinking

Google

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.

Microsoft

Phi 4 Mini

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.

Google

Gemini 2.0 Flash Thinking

Google

2025-01-21

Microsoft

Phi 4 Mini

Microsoft

2025-02-01

11 days newer

Average performance across 1 common benchmarks

Google

Gemini 2.0 Flash Thinking

+49.0%
Average Score:74.2%
Microsoft

Phi 4 Mini

Average Score:25.2%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash Thinking

general
+12.9%
73.8%
Microsoft

Phi 4 Mini

general
60.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
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

Google

Gemini 2.0 Flash Thinking

0 providers
Microsoft

Phi 4 Mini

0 providers
Google

Gemini 2.0 Flash Thinking

+49.0%
Avg Score:74.2%
Providers:0
Microsoft

Phi 4 Mini

Avg Score:25.2%
Providers:0