Model Comparison

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

Google

Gemma 3n E4B

Google

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.

Microsoft

Phi-3.5-vision-instruct

Microsoft

Phi-3.5-vision-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 68.3% across 9 benchmarks. It excels particularly in ScienceQA (91.3%), POPE (86.1%), MMBench (81.9%). The model shows particular specialization in general tasks with an average performance of 75.9%. 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 2024, it represents Microsoft's latest advancement in AI technology.

Microsoft

Phi-3.5-vision-instruct

Microsoft

2024-08-23

Google

Gemma 3n E4B

Google

2025-06-26

10 months newer

Performance comparison across key benchmark categories

Google

Gemma 3n E4B

general
59.6%
Microsoft

Phi-3.5-vision-instruct

general
+16.3%
75.9%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B

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 E4B

0 providers
Microsoft

Phi-3.5-vision-instruct

0 providers
Google

Gemma 3n E4B

Avg Score:0.0%
Providers:0
Microsoft

Phi-3.5-vision-instruct

Avg Score:0.0%
Providers:0