A Ramsey-style problem on hypergraphs has been solved by Kevin Barreto and Liam Price using GPT-5.4 Pro. The solution has been confirmed by Will Brian and will be published, along with a transcript of the original conversation.

GPT-5.4 mini and nano are newly released small models that enhance performance for high-volume workloads. GPT-5.4 mini offers over 2x faster processing and improved capabilities in coding, reasoning, multimodal understanding, and tool use, nearing the performance of the larger GPT-5.4 model in various evaluations.

GPT-5.4, now available in ChatGPT and the API, is the most capable and efficient frontier model designed for professional work. It combines advanced reasoning, coding capabilities from GPT-5.3-Codex, and enhanced agentic workflows for improved performance on complex tasks.

GPT-5.3-Codex-Spark is a new model optimized for real-time coding, capable of processing over 1000 tokens per second on ultra-low latency hardware. This model is a smaller version of GPT-5.3-Codex and represents the first milestone in a partnership with Cerebras.

A judicial experiment replicates a study on 61 U.S. federal judges using GPT-5 as the decision-maker in a hypothetical automobile accident case. The experiment manipulates three variables: the applicable doctrine as a rule or standard, and the portrayal of the plaintiff or defendant.

GPT-5.3-Codex is a new coding model that combines improved coding performance and enhanced reasoning capabilities, operating 25% faster than its predecessor, GPT-5.2-Codex. This model is designed to handle long-running tasks involving research, tool use, and complex execution, allowing for interactive steering and collaboration.

GPT-5.2 and GPT-5.2-Codex are now 40% faster due to optimizations in the inference stack for all API customers. The models maintain the same architecture and weights while offering lower latency.