Model Comparison

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

Google

Gemma 3n E2B Instructed

Google

Gemma 3n E2B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (66.5%), MMLU (60.1%), Global-MMLU-Lite (59.0%). 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 Reasoning

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.

Microsoft

Phi 4 Mini Reasoning

Microsoft

2025-04-30

Google

Gemma 3n E2B Instructed

Google

2025-06-26

1 month newer

Average performance across 1 common benchmarks

Google

Gemma 3n E2B Instructed

Average Score:24.8%
Microsoft

Phi 4 Mini Reasoning

+27.2%
Average Score:52.0%

Performance comparison across key benchmark categories

Google

Gemma 3n E2B Instructed

math
40.4%
general
32.8%
Microsoft

Phi 4 Mini Reasoning

math
+54.2%
94.6%
general
+22.0%
54.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B Instructed

2024-06-01

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

Google

Gemma 3n E2B Instructed

0 providers
Microsoft

Phi 4 Mini Reasoning

0 providers
Google

Gemma 3n E2B Instructed

Avg Score:24.8%
Providers:0
Microsoft

Phi 4 Mini Reasoning

+27.2%
Avg Score:52.0%
Providers:0