OpenAI’s new GPT-4.1 AI models focus on coding

Summary

OpenAI on Monday launched a new family of models called GPT-4.1. Yes, “4.1” — as if the company’s nomenclature wasn’t confusing enough already. There’s GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano, all of which OpenAI says “excel” at coding and instruction following. Available through OpenAI’s API but not ChatGPT, the multimodal models have a 1-million-token context window, meaning they can take in roughly 750,000 words in one go (more than “War and Peace”). GPT-4.1 arrives as OpenAI rivals like Google and Anthropic ratchet up efforts to build sophisticated programming models. Google’s recently released Gemini 2.5 Pro, which also has a 1-million-token context window, ranks highly on popular coding benchmarks. So do Anthropic’s Claude 3.7 Sonnet and Chinese AI startup DeepSeek’s upgraded V3. It’s the goal of many tech giants, including OpenAI, to train AI coding models capable of performing complex software engineering tasks. OpenAI’s grand ambition is to create an “agentic software engineer,” as CFO Sarah Friar put it during a tech summit in London last month. The company asserts its future models will be able to program entire apps end-to-end, handling aspects such as quality assurance, bug testing, and documentation writing. GPT-4.1 is a step in this direction. “We’ve optimized GPT-4.1 for real-world use based on direct feedback to improve in areas that developers care most about: frontend coding, making fewer extraneous edits, following formats reliably, adhering to response structure and ordering, consistent tool usage, and more,” an OpenAI spokesperson told TechCrunch via email. “These improvements enable developers to build agents that are considerably better at real-world software engineering tasks.” OpenAI claims the full GPT-4.1 model outperforms its GPT-4o and GPT-4o mini models on coding benchmarks including SWE-bench. GPT-4.1 mini and nano are said to be more efficient and faster at the cost of some accuracy, with OpenAI saying GPT 4.1 nano is its speediest —...