Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 30.9% higher average benchmark score. Phi-4-multimodal-instruct offers 62.5K more tokens in context window than o1-mini. Phi-4-multimodal-instruct is $14.85 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
OpenAI
o1-mini is a language model developed by OpenAI. It achieves strong performance with an average score of 71.9% across 6 benchmarks. It excels particularly in HumanEval (92.4%), MATH-500 (90.0%), MMLU (85.2%). It supports a 194K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, 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.
4 months newer
o1-mini
OpenAI
2024-09-12
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Cost per million tokens (USD)
o1-mini
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 21 common benchmarks
o1-mini
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
o1-mini
Azure
OpenAI
o1-mini
Phi-4-multimodal-instruct
o1-mini
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
DeepInfra