Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 39.0% higher average benchmark score. GPT-5 mini offers 272.0K more tokens in context window than Phi-4-multimodal-instruct. Phi-4-multimodal-instruct is $2.10 cheaper per million tokens. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
OpenAI
GPT-5 mini is a multimodal language model developed by OpenAI. It achieves strong performance with an average score of 60.0% across 5 benchmarks. It excels particularly in AIME 2025 (91.1%), HMMT 2025 (87.8%), GPQA (82.3%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. 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.
6 months newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
GPT-5 mini
OpenAI
2025-08-07
Cost per million tokens (USD)
GPT-5 mini
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 20 common benchmarks
GPT-5 mini
Phi-4-multimodal-instruct
GPT-5 mini
2024-05-30
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
GPT-5 mini
OpenAI
ZeroEval
GPT-5 mini
Phi-4-multimodal-instruct
GPT-5 mini
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
DeepInfra