OpenAI 推出 GPT-6 Sol 與 Luna,API 價格較上一代促銷價再減半OpenAI releases GPT-6 Sol and Luna, halving API prices against its own promotional rates
- 事件
- OpenAI 於 9 月 22 日推出 GPT-6 Sol 與 Luna,輸入價每百萬 Token 為 2 美元與 0.10 美元,輸出價 10 美元與 0.50 美元,較 GPT-5.6 促銷價低一半。OpenAI released GPT-6 Sol and GPT-6 Luna on 22 September. Prices are $2 and $0.10 per million input tokens and $10 and $0.50 per million output tokens, 50% below GPT-5.6 promotional rates.
- 背後
- 競爭焦點已由模型智力上限轉向代理工作流的每任務成本。OpenAI 稱降幅來自快取與推理效率改善,屬新的標準定價,而非限時促銷。Competition has shifted from the intelligence ceiling to the cost per task inside agentic workflows. OpenAI attributes the cut to caching and inference efficiency and presents it as new standard pricing, not a promotion.
我們認為價格腰斬的真正意義,是把試錯成本從專案預算裡拿掉。以往團隊因重試太貴而放棄代理項目,如今成本紅線明顯下移;但計費仍有斷點,長上下文一超標,單位成本會跳升,省下來的錢可能在這裡還回去。We believe the real significance is that it removes trial-and-error cost from the project budget. Teams used to abandon agent projects because retries were too expensive, and that line has moved down. But billing still has cliffs: exceed the long-context threshold and unit costs jump, giving back the savings.
- 對日常工作的影響
- 資訊科技主管應重估長時段代理任務的每任務成本;財務與採購須把 Token 用量納入部門預算;市場部的高頻文案與資料整理工序最先受惠。IT leads should re-estimate cost per task for long-running agent jobs; finance and procurement must put token consumption into departmental budgets. Marketing workflows for high-volume copy and data cleanup benefit first.
- 如何改善
- 本週選一條重複工序,例如資料抽取或分類,用低價模型跑一日,記錄每任務實際成本與出錯率,再決定是否擴至其他工序。This week, pick one repetitive workflow such as data extraction or classification, run it for a day on the cheap tier, and log real cost per task and error rate before extending it.
