GPT‑4.1, GPT‑4.1 Mini, and GPT‑4.1 Nano, New OpenAI Models with Context Windows with Up to 1M Tokens

OpenAI has launched three new models: GPT-4.1, GPT-4.1 Mini, and GPT-4.1 Nano, featuring larger context windows (up to 1 million tokens) and improved performance.
The GPT-4.1 model family offers exceptional performance at a lower cost compared to previous versions, with prices starting from $0.10/million input tokens for the smallest model, GPT-4.1 Nano.
GPT-4.1 nano is the fastest and cheapest model available, delivering exceptional performance with its 1 million token context window, making it suitable for tasks that demand low latency.
The new models are part of OpenAI’s ambition to create an “agentic software engineer,” a goal mentioned by CFO Sarah Friar during a tech summit in London last month.
OpenAI’s competitors, such as Google and Anthropic, have also released similar models with 1-million-token context windows, including Gemini 2.5 Pro and Claude 3.7 Sonnet, highlighting the growing competition in AI development.

IBL News | New York

OpenAI launched three new models — GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano — in its API this month, featuring larger context windows (up to 1 million tokens) and improved performance in coding and instruction over GPT‑4o and GPT‑4o mini.

“To this end, the GPT‑4.1 model family offers exceptional performance at a lower cost,” said the company.

“For tasks that demand low latency, GPT‑4.1 nano is our fastest and cheapest model available; it delivers exceptional performance at a small size with its 1 million token context window.”

Only available via the API, GPT‑4.1 arrives as OpenAI rivals like Google and Anthropic released, respectively, Gemini 2.5 Pro, which also has a 1-million-token context window, and Claude 3.7 Sonnet. Also, Chinese AI startup DeepSeek launched an upgraded V3.

“OpenAI’s ambition is to create an “agentic software engineer,” as CFO Sarah Friar put it during a tech summit in London last month.

GPT-4.1 costs $2 per million input tokens and $8 per million output tokens. GPT-4.1 mini is $0.40/million input tokens and $1.60/million output tokens, and GPT-4.1 nano is $0.10/million input tokens and $0.40/million output tokens.

OpenAI CFO Sarah Friar on the race to build artificial general intelligence (Goldman Sachs’ Disruptive Tech Summit in London on March 5, 2025)

“And then the third that is coming is what we call A-SWE. We’re not the best marketers, by the way, you might have noticed. But Agentic… https://t.co/oFd0SKGu3S

— Tibor Blaho (@btibor91) April 12, 2025

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Q. What are the names of the new models launched by OpenAI?

A. GPT-4.1, GPT-4.1 Mini, and GPT-4.1 Nano.

Q. What is the maximum context window size for these new models?

A. Up to 1 million tokens.

Q. How does the performance of GPT-4.1 compare to its predecessors (GPT-4o and GPT-4o mini)?

A. It offers improved performance in coding and instruction.

Q. What is the pricing model for GPT-4.1?

A. $2 per million input tokens and $8 per million output tokens.

Q. How does the pricing of GPT-4.1 Mini compare to GPT-4.1?

A. It costs $0.40/million input tokens and $1.60/million output tokens, which is lower than GPT-4.1.

Q. What is the pricing model for GPT-4.1 Nano?

A. $0.10/million input tokens and $0.40/million output tokens, making it the cheapest option.

Q. Who is OpenAI’s CFO mentioned in the article?

A. Sarah Friar.

Q. What is OpenAI’s ambition with its new models?

A. To create an “agentic software engineer”.

Q. How does GPT-4.1 Nano compare to other models in terms of performance and cost?

A. It is the fastest and cheapest model available, delivering exceptional performance at a small size.

Q. What are some of the rival models released by other companies?

A. Gemini 2.5 Pro (Google) and Claude 3.7 Sonnet (Anthropic).