Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 16.7% higher average benchmark score. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
Gemma 3n E2B is a multimodal language model developed by Google. The model shows competitive results across 11 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. Released in 2025, it represents Google's latest advancement in AI technology.
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%). 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.
4 months newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Gemma 3n E2B
2025-06-26
Context window and performance specifications
Average performance across 26 common benchmarks
Gemma 3n E2B
Phi-4-multimodal-instruct
Gemma 3n E2B
2024-06-01
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
Gemma 3n E2B
Phi-4-multimodal-instruct
DeepInfra
Gemma 3n E2B
Phi-4-multimodal-instruct
Gemma 3n E2B
Phi-4-multimodal-instruct