Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Gemini 2.5 Flash offers 33.8K more tokens in context window than GPT-4.1 nano. GPT-4.1 nano is $2.30 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
Gemini 2.5 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 14 benchmarks. It excels particularly in Global-MMLU-Lite (88.4%), AIME 2024 (88.0%), FACTS Grounding (85.3%). 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
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.
1 month newer
GPT-4.1 nano
OpenAI
2025-04-14
Gemini 2.5 Flash
2025-05-20
Cost per million tokens (USD)
Gemini 2.5 Flash
GPT-4.1 nano
Context window and performance specifications
Average performance across 34 common benchmarks
Gemini 2.5 Flash
GPT-4.1 nano
GPT-4.1 nano
2024-05-31
Gemini 2.5 Flash
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Flash
ZeroEval
Gemini 2.5 Flash
GPT-4.1 nano
Gemini 2.5 Flash
GPT-4.1 nano
GPT-4.1 nano
OpenAI