Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 41.5% higher average benchmark score. GPT-5 nano offers 272.0K more tokens in context window than Phi-4-multimodal-instruct. Both models have similar pricing. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
OpenAI
GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). 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 nano
OpenAI
2025-08-07
Cost per million tokens (USD)
GPT-5 nano
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 20 common benchmarks
GPT-5 nano
Phi-4-multimodal-instruct
GPT-5 nano
2024-05-30
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
GPT-5 nano
OpenAI
ZeroEval
GPT-5 nano
Phi-4-multimodal-instruct
GPT-5 nano
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
DeepInfra