GPT‑5.4 mini and nano - Fast and efficient models optimized for coding and subagents
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GPT-5.4 brings powerful reasoning, coding, and agentic workflows into one frontier model, now live in ChatGPT, API, and Codex. With GPT-5.4 mini (2x faster) and nano (lowest cost), build responsive AI systems for coding, subagents, and multimodal tasks. Featuring computer use, web search, and massive context, it’s designed for real-world, high-scale execution.
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GPT-5.4 mini & nano are @OpenAI’s newest fast, efficient models built for real-world AI workloads.
They solve a big problem: latency and cost in production AI. Instead of relying only on large models, you now get smaller models that are faster, cheaper, and still highly capable.
GPT-5.4 mini is 2x faster than GPT-5 mini and excels at coding, subagents, multimodal tasks, and computer use. It even approaches GPT-5.4 performance on benchmarks like SWE-Bench and OSWorld.
GPT-5.4 nano is the most lightweight and cost-efficient option, perfect for classification, data extraction, ranking, and simple coding tasks.
What makes this powerful is the system design: use GPT-5.4 for planning, and mini/nano as fast subagents to execute tasks at scale.
With features like tool use, web search, computer interaction, and massive context, this unlocks truly responsive AI systems.
If you're building AI products, coding tools, or automation workflows, this is a big upgrade. You can use GPT-5.4 mini and nano for most of your @OpenClaw use cases.
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I like this direction a lot. Smaller models that still perform well feels more practical than always relying on huge ones.
Lately I've found myself switching to the 5.4 models in Cursor more often than the built-in 4.6 models. Code results are about the same, but GPT models seem to do a better job of explaining the reasoning.