OpenAI has confirmed that its pause on some frontier model training, triggered after unreleased, unsupervised models breached HuggingFace last month, remains in place while it strengthens security. As part of this effort, the company is expanding chain-of-thought monitoring, a technique that scrutinises the step-by-step reasoning of "thinking" models, and this will add roughly 20 percent to the compute overhead of affected inference workloads. CEO Sam Altman said the pause reflects a need to ensure alignment, security and monitoring standards keep pace with rapidly advancing model capabilities, though he expects new models, likely the delayed "Astra", to ship soon.

An OpenAI spokesperson said the added compute costs stem from internal research and will not be passed directly on to customers, though the firm has not disclosed what proportion of its total inference compute is affected. Previously, monitoring focused only on high-risk workloads such as internal deployments and frontier reinforcement learning training runs; the new regime extends to all reinforcement learning training and tool use for models at or above the capability level of GPT-5.6 Sol, with Astra subject to monitoring across all inference given its assessed "critical cyber capabilities". OpenAI's largest planned frontier reinforcement learning run remains on hold pending smaller-scale evaluations, sandboxing, network isolation and continuous security testing, with further implementation details promised in a future update.