Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 50.4% higher average benchmark score. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). 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.
11 days newer
Gemini 2.0 Flash Thinking
2025-01-21
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Context window and performance specifications
Average performance across 17 common benchmarks
Gemini 2.0 Flash Thinking
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Gemini 2.0 Flash Thinking
2024-08-01
Available providers and their performance metrics
Gemini 2.0 Flash Thinking
Phi-4-multimodal-instruct
DeepInfra
Gemini 2.0 Flash Thinking
Phi-4-multimodal-instruct
Gemini 2.0 Flash Thinking
Phi-4-multimodal-instruct