GPT‑5.4 nano is the smallest, cheapest version of GPT‑5.4 for tasks where speed and cost matter most. It is also a significant upgrade over GPT‑5 nano. We recommend it for classification, data extraction, ranking, and coding subagents that handle simpler supporting tasks.

These models are built for the kinds of workloads where latency directly shapes the product experience: coding assistants that need to feel responsive, subagents that quickly complete supporting tasks, computer-using systems that capture and interpret screenshots, and multimodal applications that can reason over images in real-time. In these settings, the best model is often not the largest one—it’s the one that can respond quickly, use tools reliably, and still perform well on complex professional tasks.

Here’s what our customers think after testing GPT‑5.4 mini and nano in their workflows:

GPT‑5.4 mini and nano are especially effective in coding workflows that benefit from fast iteration. The models handle targeted edits, codebase navigation, front-end generation, and debugging loops with low latency, making them a strong fit for coding tasks that need to be completed at faster speeds and lower costs.