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模型詳情

gpt-5.4-nano

由 OpenAI 提供
隨用隨付

GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency use cases such as classification, data extraction, ranking, and sub-agent execution. The model prioritizes responsiveness and efficiency over deep reasoning, making it ideal for pipelines that require fast, reliable outputs at scale. GPT-5.4 nano is well suited for background tasks, real-time systems, and distributed agent architectures where minimizing cost and latency is essential.

模型規格

上下文長度
400K
最大輸出
128K
輸入/輸出模態
文字 / 圖片
發布日期
2026-03

02

API 端點

單一 MixRoute 閘道,OpenAI 相容

  • OpenAI-compatible /v1/chat/completions POST

03

價格

固定費率,單位:/1M Tokens

輸入

$0.2000 /1M Tokens

補全

$1.2500 /1M Tokens

快取讀取

$0.0200 /1M Tokens

05

選型摘要

快速判斷是否適合你的工作負載

What is this model good for?

Start with the documented use cases for gpt-5.4-nano

GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency use cases such as classification, data extraction, ranking, and sub-agent execution. The model prioritizes responsiveness and efficiency over deep reasoning, making it ideal for pipelines that require fast, reliable outputs at scale. GPT-5.4 nano is well suited for background tasks, real-time systems, and distributed agent architectures where minimizing cost and latency is essential.

What should you check before using it?

Validate limits, pricing, and a representative workload

Review the current model limits and pricing record before production use.

How do you call it through MixRoute?

Use the documented endpoint and exact model ID

The model record lists OpenAI-compatible access via POST /v1/chat/completions with model ID gpt-5.4-nano.

08

Token 成本估算

基於本頁價格的即時估算,非實際帳單

同一前綴被重複讀取的輸入占比,最高 100%

單一端點,可驗證的決策

使用相同的請求格式測試此模型與替代路由

從真實工作負載開始,再由品質、總成本與故障條件決定是否導入正式環境流量。