Yesterday, OpenAI unveiled its new GPT-4.1 model family, which includes GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano. These models promise significantly improved coding, instruction following, and long-context understanding compared to earlier versions like GPT-4o. All three support up to one million tokens of context, so they can handle much larger documents, codebases, or even hour-long video transcripts. In coding tests, GPT-4.1 scored 54.6% on the SWE-bench Verified benchmark, a jump of 21.4 points over GPT-4o. That makes it one of the strongest models for real-world software engineering tasks. It's better at exploring code repositories, creating patches that actually compile and pass tests, and following diff formats without extra edits. Areas like instruction following got a boost, too. On Scale's MultiChallenge benchmark, GPT-4.1 scored 38.3%, up 10.5 points from GPT-4o. That means it can stick to multi-step prompts more reliably and format its responses the way you ask.

The models' long-context skills stand out on the Video-MME benchmark, where GPT-4.1 scored 72.0% in the "long, no subtitles" category, 6.7 points higher than GPT-4o. Thanks to its one-million-token window, GPT-4.1 can pull together information spread across huge inputs, whether it's scattered text in a document or key moments in a video. OpenAI says these gains come from close work with developers, tuning the models for tasks that matter while cutting costs and latency. GPT-4.1 mini cuts cost 83% and nearly half the response time compared to GPT-4o. GPT-4.1 nano is even faster and cheaper, making it ideal for classification or autocompletion. All three models are available now through OpenAI's API. They won't appear directly in ChatGPT initially, though many of their improvements have already made it into the latest GPT-4o chatbot. Developers using the GPT-4.5 Preview should plan to switch over by July 14, 2025, when that version will be retired. While o3-mini remains the most powerful thinking model, the non-thinking GPT-4.1 family is closing the gap to deliver faster response times.