OpenAI today launches GPT-5.4 mini and GPT-5.4 nano, two smaller versions of its GPT-5.4 family designed for when speed and cost matter as much as quality. What are they really for? For letting code assistants, subagents and multimodal apps respond smoothly without always needing the biggest model.
What’s new
GPT-5.4 mini improves over the previous generation (GPT-5 mini) in several areas: reasoning, code handling, multimodal understanding and reliable tool use, and it also runs more than 2x faster on many workloads. GPT-5.4 nano is the smallest and most economical option, ideal when latency and low cost are the top priorities.
Both models are built for scenarios where latency shapes the experience: code assistants that must feel instant, subagents that complete support tasks in parallel, systems that interpret screenshots, and multimodal apps that reason about images in real time.
Performance in clear terms
I won’t drown you in tables, but I will give you the numbers that matter so you can compare quickly:
