Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 14.0% higher average benchmark score. GPT-4.1 nano offers 1.0M more tokens in context window than Gemini 1.0 Pro. GPT-4.1 nano is $1.50 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Overall, GPT-4.1 nano is the stronger choice for coding tasks.
Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. 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.
1 year newer
Gemini 1.0 Pro
2024-02-15
GPT-4.1 nano
OpenAI
2025-04-14
Cost per million tokens (USD)
Gemini 1.0 Pro
GPT-4.1 nano
Context window and performance specifications
Average performance across 30 common benchmarks
Gemini 1.0 Pro
GPT-4.1 nano
Gemini 1.0 Pro
2024-02-01
GPT-4.1 nano
2024-05-31
Available providers and their performance metrics
Gemini 1.0 Pro
GPT-4.1 nano
Gemini 1.0 Pro
GPT-4.1 nano
Gemini 1.0 Pro
GPT-4.1 nano
OpenAI