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

Gemma 3n E2B Instructed
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.

Phi-4-multimodal-instruct
Microsoft
Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). The model shows particular specialization in general tasks with an average performance of 75.8%. It supports a 256K token context window for handling large documents. The model is available through 1 API provider. 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 Microsoft's latest advancement in AI technology.

Phi-4-multimodal-instruct
Microsoft
2025-02-01

Gemma 3n E2B Instructed
2025-06-26
4 months newer
Performance Metrics
Context window and performance specifications

Gemma 3n E2B Instructed

Phi-4-multimodal-instruct
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed

Phi-4-multimodal-instruct
Gemma 3n E2B Instructed
2024-06-01
Phi-4-multimodal-instruct
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B Instructed

Phi-4-multimodal-instruct
DeepInfra

Gemma 3n E2B Instructed

Phi-4-multimodal-instruct