Comprehensive side-by-side LLM comparison
o3-mini leads with 9.8% higher average benchmark score. o3-mini offers 44.0K more tokens in context window than Phi-4-multimodal-instruct. Phi-4-multimodal-instruct is $5.35 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Overall, o3-mini is the stronger choice for coding tasks.
OpenAI
o3-mini is a language model developed by OpenAI. The model shows competitive results across 26 benchmarks. It excels particularly in COLLIE (98.7%), MATH (97.9%), IFEval (93.9%). It supports a 300K token context window for handling large documents. The model is available through 2 API providers. Released in 2025, it represents OpenAI'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.
2 days newer
o3-mini
OpenAI
2025-01-30
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Cost per million tokens (USD)
o3-mini
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 41 common benchmarks
o3-mini
Phi-4-multimodal-instruct
o3-mini
2023-09-30
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
o3-mini
Azure
OpenAI
o3-mini
Phi-4-multimodal-instruct
o3-mini
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
DeepInfra