GPT-5-Mini keeps the full developer surface—272 k / 128 k context, reasoning_effort, verbosity, custom tools, and multimodal support—while dialing down active experts to slash latency and memory. In internal measurements it replies roughly 40 % faster than the flagship yet still registers 91.1 % on the 2025 AIME math contest and 87.8 % on OpenAI’s aggregate “Intelligence” suite, comfortably outperforming o3 and rival compact models. The smaller footprint is ideal for high-traffic chat widgets, knowledge-base summarisation, edge analytics, and mobile agents where per-request cost dominates. Mini inherits GPT-5’s safer completion style and reduced hallucinations, making it suitable for customer-facing scenarios that once demanded the full model. Pricing lands at just US $0.25 / M input tokens and US $2 / M output tokens, so migrating from the flagship is as easy as swapping the model name and rerunning load tests. (OpenAI)