Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance

Gemini 2.5 Pro
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 67.1% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). The model shows particular specialization in vision tasks with an average performance of 82.2%. With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. 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.

GPT-4.1 nano
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. 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.

GPT-4.1 nano
OpenAI
2025-04-14

Gemini 2.5 Pro
2025-05-20
1 month newer
Pricing Comparison
Cost per million tokens (USD)

Gemini 2.5 Pro

GPT-4.1 nano
Performance Metrics
Context window and performance specifications

Gemini 2.5 Pro

GPT-4.1 nano
Average performance across 5 common benchmarks

Gemini 2.5 Pro

GPT-4.1 nano
Performance comparison across key benchmark categories

Gemini 2.5 Pro

GPT-4.1 nano
GPT-4.1 nano
2024-05-31
Gemini 2.5 Pro
2025-01-31
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.5 Pro

GPT-4.1 nano
OpenAI

Gemini 2.5 Pro

GPT-4.1 nano