Expanding its latest AI lineup, OpenAI has introduced 2 new models under the GPT-5.4 family. Named GPT-5.4 mini and GPT-5.4 nano, these models are designed for faster performance and low-latency workloads.
Both models focus on key strengths such as coding, computer use, multimodal understanding, and subagent handling. They are also built to be cost-efficient for developers due to lower input and output token pricing.
According to the company, GPT-5.4 mini is available via API, Codex, and ChatGPT. It supports text and image inputs, tool use, function calling, web search, file search, computer use, and skills.
The model comes with a 400,000 token context window. Pricing is set at $0.75 per 1M input tokens and $4.50 per 1M output tokens.
GPT-5.4 mini is accessible to free and Go tier users through the Thinking feature. Other users will see it as a fallback model after reaching the limit for GPT-5.4 Thinking.
GPT-5.4 nano, on the other hand, is currently available only via API. It is priced at $0.20 per 1M input tokens and $1.25 per 1M output tokens.
Both models are optimised for coding tasks in fast and iterative environments. OpenAI says, “handle targeted edits, codebase navigation, front-end generation, and debugging loops with low latency.”
The company also states that GPT-5.4 mini outperforms GPT-5-mini in most areas while maintaining similar latency levels.
A key capability of these models is subagent handling. While larger models manage complex tasks like planning and coordination, the mini version can handle smaller subtasks in parallel.
This allows developers to build systems where a single model does not need to manage every step in an agent workflow.
OpenAI also highlights strong performance in multimodal tasks related to computer use. On the OSWorld-Verified benchmark, the mini variant performs close to GPT-5.4.
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