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OpenAI Releases GPT-5.4 mini and nano Models

OpenAI Releases GPT-5.4 mini and nano Models

@shao__meng

OpenAI 推出 GPT-5.4 mini 和 GPT-5.4 nano

GPT-5.4 mini 比 GPT-5 mini 速度提升 2+ 倍，在多项核心能力上显著升级，同时接近完整版 GPT-5.4 的表现，尤其在以下场景深度优化：

· 编程与代码生成

· 计算机使用（Computer Use）

· 多模态理解（文本 + 图像输入）

· Subagents 协作与工具调用

在 SWE-Bench Pro、OSWorld-Verified 等基准上已逼近旗舰级 GPT-5.4，非常适合高频、高吞吐的 Agent 工作流、日常编码和复杂推理任务。

GPT-5.4 mini 已同步上线 API、Codex 和 ChatGPT：

· API 支持 400k 上下文窗口（支持文本 + 图像输入）

· 在 Codex 中仅消耗完整 GPT-5.4 配额的 30%，让开发者能以约 1/3 成本 处理常见编码任务，特别适合日常开发和高频调用

GPT-5.4 nano 更适合更轻量、成本敏感的任务，它是 GPT-5.4 家族中体积最小、价格最低的版本。它在速度与经济性上极致优化，显著优于前代 nano，推荐用于：

· 分类

· 数据抽取

· 排序

· 简单辅助编码 Subagents

GPT-5.4 nano 目前仅在 API 中提供，专为极致速度与成本优化的场景设计。Show More

!Image 3: Tweet image

!Image 4: OpenAI Developers

#### OpenAI Developers

@OpenAIDevs · 19h ago

We’re introducing GPT-5.4 mini and nano, our most capable small models yet.

GPT-5.4 mini is more than 2x faster than GPT-5 mini. Optimized for coding, computer use, multimodal understanding, and subagents.

For lighter-weight tasks, GPT-5.4 nano is our smallest and cheapest version of GPT-5.4. openai.com/index/introduc…Show More

!Image 5: Tweet image

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Mar 18, 2026, 12:33 AM View on X

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1,555 Views  meng shao @shao__meng

One Sentence Summary

OpenAI has launched the significantly enhanced GPT-5.4 mini and the lighter, more cost-effective GPT-5.4 nano models, optimizing capabilities in areas such as programming, multimodal understanding, and Agent collaboration.

Summary

This tweet details OpenAI's newly released GPT-5.4 mini and GPT-5.4 nano, two compact models. GPT-5.4 mini boasts over twice the speed of its predecessor and features deep optimizations in programming, computer use, multimodal understanding, and Subagent collaboration. Its performance approaches that of the flagship GPT-5.4, making it ideal for high-frequency Agent workflows and complex reasoning tasks, while costing only one-third of the full GPT-5.4's quota in Codex. The GPT-5.4 nano is the smallest and most economical version in the family, specifically designed for lightweight, cost-sensitive tasks such as classification and data extraction. These new models aim to provide more efficient and economical AI solutions, catering to the diverse needs of developers.

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