Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. GPT-4.1 nano offers 23.6K more tokens in context window than Gemini 2.0 Flash. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). 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 2024, 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.
4 months newer
Gemini 2.0 Flash
2024-12-01
GPT-4.1 nano
OpenAI
2025-04-14
Cost per million tokens (USD)
Gemini 2.0 Flash
GPT-4.1 nano
Context window and performance specifications
Average performance across 36 common benchmarks
Gemini 2.0 Flash
GPT-4.1 nano
GPT-4.1 nano
2024-05-31
Gemini 2.0 Flash
2024-08-01
Available providers and their performance metrics
Gemini 2.0 Flash
GPT-4.1 nano
Gemini 2.0 Flash
GPT-4.1 nano
Gemini 2.0 Flash
GPT-4.1 nano
OpenAI