OpenAI launched new open weight models designed for agentic AI workflows. These models boast a 128K token context window, letting users process much longer texts—think customer service transcripts, technical docs, academic papers.
The models handle complex tasks with advanced reasoning, breaking problems into chain-of-thought steps. Use cases include coding, scientific analysis, math problem-solving, and more.
They support instruction-following and tool use like web search and code interpreter for real-time data and multi-step tasks. Safety is a big focus; each model went through extensive safety training and evaluation. 
“As organizations increasingly embrace agentic AI, they need a variety of models capable of executing complex tasks. OpenAI’s open weight models meet this need with a compelling performance-to-size ratio and advanced reasoning, including adjustable reasoning levels and chain-of-thought outputs that break down complex problems into logical steps. This makes them great for use cases like agentic workflows, coding, scientific analysis, and mathematical problem-solving. These models support instruction-following and tool use—web search and code interpreter—to help them reference real-time information and perform multi-step tasks. Featuring a 128K context input window, these text-generation models enable customers to process longer documents and conversations, such as customer service transcripts, detailed technical documentation, academic papers, and more. Safety is a central component of the open weight models, and to support the responsible deployment of generative AI applications, each model has undergone comprehensive safety training and evaluation by OpenAI.”
