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

Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3n E2B Instructed LiteRT (Preview) is a multimodal language model developed by Google. The model shows competitive results across 28 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.

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.

Phi 4 Mini
Microsoft
2025-02-01

Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20
3 months newer
Average performance across 11 common benchmarks

Gemma 3n E2B Instructed LiteRT (Preview)

Phi 4 Mini
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed LiteRT (Preview)

Phi 4 Mini
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Phi 4 Mini
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B Instructed LiteRT (Preview)

Phi 4 Mini

Gemma 3n E2B Instructed LiteRT (Preview)

Phi 4 Mini