Model Comparison

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

Google

Gemma 3n E2B

Google

Gemma 3n E2B is a multimodal language model developed by Google. The model shows competitive results across 11 benchmarks. Notable strengths include PIQA (78.9%), BoolQ (76.4%), ARC-E (75.8%). 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.

Microsoft

Phi 4 Mini

Microsoft

2025-02-01

Google

Gemma 3n E2B

Google

2025-06-26

4 months newer

Average performance across 7 common benchmarks

Google

Gemma 3n E2B

Average Score:62.7%
Microsoft

Phi 4 Mini

+11.8%
Average Score:74.5%

Performance comparison across key benchmark categories

Google

Gemma 3n E2B

reasoning
66.6%
general
54.1%
Microsoft

Phi 4 Mini

reasoning
+6.6%
73.3%
general
+6.7%
60.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B

2024-06-01

Phi 4 Mini

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 3n E2B

0 providers
Microsoft

Phi 4 Mini

0 providers
Google

Gemma 3n E2B

Avg Score:62.7%
Providers:0
Microsoft

Phi 4 Mini

+11.8%
Avg Score:74.5%
Providers:0