Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance
Gemma 3n E4B
Gemma 3n E4B is a multimodal language model developed by Google. It achieves strong performance with an average score of 64.6% across 11 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). 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.
Phi-3.5-mini-instruct
Microsoft
Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Gemma 3n E4B
2025-06-26
10 months newer
Performance Metrics
Context window and performance specifications
Gemma 3n E4B
Phi-3.5-mini-instruct
Average performance across 7 common benchmarks
Gemma 3n E4B
Phi-3.5-mini-instruct
Performance comparison across key benchmark categories
Gemma 3n E4B
Phi-3.5-mini-instruct
Gemma 3n E4B
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics
Gemma 3n E4B
Phi-3.5-mini-instruct
Azure
Gemma 3n E4B
Phi-3.5-mini-instruct