Comprehensive side-by-side LLM comparison
o3-mini leads with 10.2% higher average benchmark score. Gemini 2.5 Pro offers 814.1K more tokens in context window than o3-mini. o3-mini is $5.75 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, o3-mini is the stronger choice for coding tasks.
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 Google's latest advancement in AI technology.
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.
3 months newer
o3-mini
OpenAI
2025-01-30
Gemini 2.5 Pro
2025-05-20
Cost per million tokens (USD)
Gemini 2.5 Pro
o3-mini
Context window and performance specifications
Average performance across 36 common benchmarks
Gemini 2.5 Pro
o3-mini
o3-mini
2023-09-30
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Pro
ZeroEval
Gemini 2.5 Pro
o3-mini
Gemini 2.5 Pro
o3-mini
o3-mini
Azure
OpenAI