登入 預約諮詢
AiX 環球 AI 情報 Global AI Intelligence
第 2 期 2026 年 9 月 26 日(星期六) 07:30 出刊 10 條情報 · 13 原文來源連結 RSS 過往期數

今日十條 · 2026 年 9 月 26 日成本下降、責任上升:模型連環減價與監管同步收網的一日

今日主編判斷

今日十條的共同主線是:AI 的成本正在下降,責任卻在上升。前沿模型在四十八小時內連環減價,內地同日以 1.6 兆參數模型加入長任務競賽;另一邊廂,歐盟啟動首輪合規巡查,內地要求智能體安全可控貫穿全周期,日本監管機構開始審視數據中心融資,香港的人力推算則把入職階梯收窄寫成具體數字。我們認為,企業今年的分水嶺不在買哪一個模型,而在有沒有人為每一項已上線的 AI 工序簽名。One thread runs through all ten stories today: the cost of AI is falling while accountability is rising. Frontier models cut prices repeatedly within forty-eight hours, and a Chinese platform entered the long-horizon agent race the same day with a 1.6-trillion-parameter model. Meanwhile the EU opened its first compliance inspections, mainland authorities required agent safety to be controlled across the full lifecycle, Japan's regulator began scrutinising data-centre financing, and Hong Kong's manpower projection put hard numbers on how narrow the entry-level ladder has become. Our judgement: this year's dividing line is not which model you buy, but whether anyone has signed their name to each AI process already in production.

今日十條

本欄由 AIX Society 編輯部整理公開資料後撰稿,每條均附原始來源連結;事實與觀點分列,觀點屬本會判斷。

按受眾篩選

Anthropic 與 OpenAI 同日減價,前沿模型 API 定價腰斬Anthropic and OpenAI cut prices on the same day, halving frontier API rates

影響力已在發生Happening now企業決策者Business owners資訊科技IT
事件
Anthropic 推出 Claude Opus 5.5,輸入每百萬 token 4 美元;OpenAI 同日推出 GPT-6 Sol 與 Luna,定價為上代一半。Anthropic released Claude Opus 5.5 at $4 per million input tokens; OpenAI launched GPT-6 Sol and Luna the same day at half the price of their predecessors.
背後
兩家前沿實驗室在 48 小時內接連減價。當能力差距收窄,價格就成為選型分水嶺;推理與快取成本下降,令過去因太貴而擱置的流程重新成立。Two frontier labs cut prices within forty-eight hours of each other. Once capability gaps narrow, price becomes the dividing line in selection, and cheaper inference and caching make workflows shelved as too expensive viable again.
顧問觀點

我們認為減價不是好消息本身,而是門檻重設。真正的分野在於企業能否把省下來的成本換成新增的工序,否則帳單下降只會變成另一個沒有業主的預算項目。We see the cuts not as good news in themselves but as a reset of the threshold. What separates companies is whether they can convert saved cost into additional process; otherwise a smaller bill simply becomes another budget line with no owner.

對日常工作的影響
企業決策者須重算 Agent 與文件工序的單件成本;資訊科技要改寫模型路由規則,把長上下文與快取密集的工作轉到新價格層。Owners need to recalculate the cost per task for agent and document workflows, while IT must rewrite model-routing rules and move long-context, cache-heavy work onto the new price tier.
如何改善
本週揀一條最貴的提示鏈,用新模型各跑一次,比較完成率與單件成本,再決定是否換線。This week, take your most expensive prompt chain, run it once on each new model, compare completion rate against cost per task, and decide whether to switch.

美團發布 LongCat-2.5-Preview,1.6 兆參數主打長流程 AgentMeituan ships LongCat-2.5-Preview, a 1.6-trillion-parameter model aimed at long-horizon agents

影響力已在發生Happening now資訊科技IT企業決策者Business owners
事件
美團推出原生多模態模型 LongCat-2.5-Preview,混合專家架構總參數 1.6 兆、活躍約 480 億,支援 100 萬 token 上下文。Meituan released LongCat-2.5-Preview, a natively multimodal mixture-of-experts model with 1.6 trillion total parameters and roughly 48 billion active, supporting a one-million-token context window.
背後
內地大廠正把競爭焦點由對話轉向可自主操作瀏覽器、試算表與終端的長流程任務;此次刻意不公布基準分數,反映市場已由跑分轉向實際可用性。Chinese platform companies are shifting the contest from conversation to long-horizon tasks that operate browsers, spreadsheets and terminals. The deliberate omission of benchmark scores signals a market moving from league tables to practical usability.
顧問觀點

我們認為真正值得留意的是「不公布跑分」這個動作。當廠商不再用分數說服客戶,採購的判斷責任就回到企業身上,你要自己有一套業務場景的驗收方法。What deserves attention is the decision not to publish benchmarks. Once vendors stop persuading buyers with scores, the burden of judgement returns to the enterprise: you need your own acceptance test built on your own business scenarios.

對日常工作的影響
資訊科技若考慮引入低成本內地模型,須先建立自己的任務驗收清單;市場與營運可先試用其試算表及瀏覽器操作自動化。IT teams considering low-cost mainland models must first build their own task acceptance checklist, while marketing and operations can pilot the spreadsheet and browser automation features.
如何改善
本週挑三個每天在做、步驟固定的文書工序,用一個國產模型試做,記錄出錯位置作為採購依據。This week, pick three fixed-step paperwork routines you perform daily, run them through one mainland model, and record where it fails as the basis for procurement.

小米開源 MiMo-V2.6-Pro 登頂,開放權重模型已佔 token 用量 56%Xiaomi's open-sourced MiMo-V2.6-Pro tops the charts as open weights reach 56% of token volume

影響力已在發生Happening now資訊科技IT企業決策者Business owners
事件
小米開源 MiMo-V2.6-Pro,1.02 兆參數,智能指數 46 分居開源權重首位;開放權重模型已佔全球 token 用量 56%。Xiaomi open-sourced MiMo-V2.6-Pro, a 1.02-trillion-parameter model scoring 46 on the Artificial Analysis Intelligence Index to lead open-weight models; open-weight models now account for 56% of token volume.
背後
開放權重模型由「便宜替代品」變成在智能密度與成本上同時領先,直接削弱閉源模型的定價能力,也令企業部署可以留在自家或內地雲環境之內。Open-weight models have moved from cheap substitutes to leading on both intelligence density and cost, weakening closed-model pricing power and letting enterprises keep deployment inside their own or mainland cloud environments.
顧問觀點

我們認為對中小企而言,這一條的意義是選擇權回來了。當開源模型在同等任務上只及閉源幾分之一成本,租用閉源 API 就必須提出可證明的理由,而不是默認選項。For smaller firms, the significance is that choice has returned. When an open model costs a fraction of a closed one on the same task, renting closed APIs must be justified rather than assumed.

對日常工作的影響
資訊科技主管要重新檢視推論成本與資料落地要求;若涉及客戶資料或個資,本地或私有部署的可行性已明顯提高。IT leaders should revisit inference cost and data-residency requirements; where customer or personal data is involved, local or private deployment is now far more viable.
如何改善
本週在一台現有伺服器上試跑一個開源權重模型,用公司真實文件測試,量度回應質素與硬件成本。This week, run one open-weight model on an existing server, test it on real company documents, and measure answer quality against hardware cost.

歐盟 AI 法案首輪合規巡查,聚焦招聘篩選與信貸評分The EU's first AI Act inspections target resume screening and credit scoring

影響力已在發生Happening now法務合規Legal & compliance人力資源HR企業決策者Business owners
事件
歐盟人工智能辦公室聯同 24 個成員國監管機構展開首輪合規巡查,對象為自動履歷篩選、算法信貸評分與醫療分流工具。The European AI Office, working with 24 national market surveillance authorities, has begun its first wave of compliance inspections covering automated resume screening, algorithmic credit scoring and healthcare triage tools.
背後
高風險系統的合規期限已延至 2027 年 12 月,但透明度義務沒有跟著延後。監管機構先以正式資料索取開場,把舉證壓力先放到企業身上。The deadline for high-risk system compliance was pushed to December 2027, but the transparency duty was not. Regulators are opening with formal requests for information, placing the burden of proof on companies first.
顧問觀點

我們認為企業最容易誤判的地方,是以為還有十六個月。真正要現在處理的,是「你在甚麼環節用了 AI 而沒有告訴對方」這一條。The most common misjudgement is assuming sixteen months of breathing room. What must be handled now is the narrower question of where you use AI without telling the person on the other side.

對日常工作的影響
人力資源與法務要盤點所有自動篩選、評分與排序流程,包括用試算表做的;市場部門要檢查聊天機械人有否表明身分。HR and legal must inventory every automated screening, scoring and ranking process, spreadsheets included, while marketing should check that chatbots disclose they are machines.
如何改善
本週列出公司所有自動篩選或評分流程,逐項寫明用途、負責人與告知方式,作為問卷回覆底稿。This week, list every automated screening or scoring process, noting its purpose, owner and how users are informed, as the draft for your questionnaire response.

內地《人工智能安全治理框架 3.0》把智能體風險納入治理主線China's AI Safety Governance Framework 3.0 brings agent risk into the mainstream

影響力6–12 個月6–12 months資訊科技IT法務合規Legal & compliance企業決策者Business owners
事件
內地發布《人工智能安全治理框架 3.0》,首次設專門章節處理智能體風險,並要求安全可控貫穿研發、部署與應用全周期。China released version 3.0 of its AI Safety Governance Framework, adding the first dedicated section on agentic AI risk and requiring safety controls across the full lifecycle of development, deployment and use.
背後
智能體能自主感知、調用工具、執行操作,風險由「答錯」變成「做錯」。主管部門於是把分類分級、備案、安全檢測與問題召回,延伸到供應鏈與權限環節。Because agents perceive, call tools and act on their own, risk moves from answering wrongly to doing wrongly. Regulators are therefore extending classification, filing, safety testing and recall duties into supply chains and permission layers.
顧問觀點

我們認為這一條對在內地營運的企業比歐盟法案更貼身。框架不是法律,但它是執法與採購的語言,寫標書與做驗收時會直接引用。For companies operating on the mainland this matters more directly than the EU Act. The framework is not statute, but it is the language of enforcement and procurement, cited directly in tenders and acceptance reviews.

對日常工作的影響
資訊科技與法務要為每個在跑的智能體登記擁有者、權限範圍與停用條件;政務、金融等高風險場景要預備備案與檢測材料。IT and legal should register an owner, an access scope and a kill condition for every running agent, and prepare filing and testing material for high-risk settings such as government and finance.
如何改善
本週為每一隻在跑的智能體開一份檔案,填不出擁有者與權限範圍的,先降權或停用。This week, open a file for every agent in production; where the owner or access scope cannot be named, reduce its permissions or switch it off.

上海金融監管局推十六項措施,探索大模型直接面客試點Shanghai's banking regulator issues sixteen measures and a pilot path for customer-facing models

影響力6–12 個月6–12 months企業決策者Business owners法務合規Legal & compliance前線員工Frontline staff
事件
上海金融監管局印發銀行業保險業人工智能應用若干措施,推出十六項舉措,並探索建立生成式大模型在金融領域應用的試點機制。Shanghai's financial regulator issued measures on AI adoption in banking and insurance, setting out sixteen initiatives and exploring a pilot mechanism for applying generative models in finance.
背後
大模型過去只能留在風控、投研、知識管理等後台環節;文件首次容許在可控環境下逐步直接面客,並與網信部門的備案與應用登記機制銜接。Generative models had been confined to back-office risk, research and knowledge work. The document allows a gradual move to direct customer contact inside a controlled environment, linked to existing model filing and registration rules.
顧問觀點

我們認為「可控環境」四個字是整份文件的關鍵。它既是開放,也是定價:先行先試可以,但責任界定、模型可解釋性與外包風險,都要企業自己交代清楚。The phrase controlled environment is the crux. It is both an opening and a price: you may pilot first, but you must account for responsibility boundaries, model explainability and outsourcing risk yourself.

對日常工作的影響
合規與資訊科技要建立高風險場景准入機制;客戶服務與市場部門要為面客型智能體準備披露話術與人工接手流程。Compliance and IT must establish admission controls for high-risk use cases, while service and marketing teams need disclosure scripts and a human handover path for customer-facing agents.
如何改善
本週挑一個現有面客流程,寫下若改用大模型輔助,誰負責、如何記錄、出事時如何回到人工。This week, take one existing customer-facing process and write down who is accountable, how it is logged, and how work returns to a human if something goes wrong.

香港人力推算:AI 令初級職位空缺較 2022 年少約六成Hong Kong's manpower projection: entry-level vacancies down about 60% since 2022

影響力已在發生Happening now人力資源HR企業決策者Business owners前線員工Frontline staff
事件
勞工及福利局公布人力推算中期更新,本港人力短缺由 18 萬收窄至 13 萬,適合應屆畢業生的職位空缺較 2022 年少約六成。The Labour and Welfare Bureau's mid-term manpower projection update shows the overall manpower shortfall narrowing from 180,000 to 130,000, with vacancies suitable for fresh graduates down about 60% against 2022.
背後
報告同時指出,約兩至三成職位(主要為文書)將因 AI 應用重組,7 萬名 45 至 54 歲、沒有大專學歷的中齡文書支援人員面臨轉型壓力。The report also says roughly 20% to 30% of positions, mostly clerical, will be restructured by AI adoption, and about 70,000 clerical support workers aged 45 to 54 without post-secondary education face transition pressure.
顧問觀點

我們認為這一條最重要的訊息不是「AI 搶飯碗」,而是入職階梯正在變窄。企業若不主動重建初級職位的訓練內容,三年後會發現無人可升。The key message is not that AI is taking jobs but that the entry ladder is narrowing. A company that does not rebuild what a junior role trains will find, three years from now, that it has no one to promote.

對日常工作的影響
人力資源要重新設計初級職位的職責與培訓路徑;部門主管要把例行工作交給 AI,把新人放在判斷與客戶接觸的位置。HR should redesign junior roles and their training paths, while line managers move routine work to AI and place newcomers where judgement and client contact happen.
如何改善
本週為一個初級職位重寫職務說明,刪去已被工具取代的工序,補上一項由新人負責的判斷工作。This week, rewrite one junior job description: delete the steps a tool now handles, and add one judgement task the newcomer owns.

高盛:AI 帶動的招聘放緩集中於客服、軟件、顧問與廣告Goldman Sachs: AI-related hiring slowdown is concentrated in call centres, software, consulting and advertising

影響力已在發生Happening now人力資源HR企業決策者Business owners前線員工Frontline staff
事件
高盛研究報告指美國客服中心就業較趨勢低 39%,加拿大低 33%,德國低 27%;軟件出版、管理顧問與廣告服務亦見類似收縮。A Goldman Sachs research report puts call-centre employment 39% below trend in the United States, 33% below in Canada and 27% below in Germany, with software publishing, management consulting and advertising showing similar contractions.
背後
報告認為衝擊目前集中在已具備自動化工具的知識型服務業,而非全面裁員;同期職位增長則見於需要 AI 技能的新職種,兩者同時發生。The report argues the impact is concentrated in knowledge-service industries where automation tools already exist rather than in economy-wide layoffs, while growth continues in new roles requiring AI skills.
顧問觀點

我們認為企業不應把這份報告讀成裁員預告,而應讀成職能重估。當同一份工作的一半可以被工具承接,職位設計就必須重寫,而不是等人自然流失。This should be read not as a layoff forecast but as a revaluation of functions. When half of a job can be carried by a tool, the role must be redesigned rather than left to erode through attrition.

對日常工作的影響
客戶服務與市場主管要重新界定人手編制與工具比例;人力資源在做年度預算時,應把部分招聘名額改為工具與訓練額度。Service and marketing heads should redefine headcount against tool capacity, and HR should convert part of next year's hiring budget into tooling and training allocation.
如何改善
本週統計一個團隊最近三個月的產出量,對比同期人手,算出每人可承接的實際上限。This week, count one team's output over the past three months against headcount, and calculate the real per-person ceiling.

Anthropic 洽租最高 1 吉瓦算力,單吉瓦資本投入至少 400 億美元Anthropic in talks to lease up to 1GW of compute, at least $40bn of capital per gigawatt

影響力6–12 個月6–12 months企業決策者Business owners資訊科技IT
事件
據報 Anthropic 洽談向 Stream Data Centers 租用最高 1 吉瓦算力,並討論部署 Google 與博通設計的 TPU。Anthropic is reported to be in talks to lease up to one gigawatt of capacity from Stream Data Centers, discussing deployment of TPUs designed by Google and Broadcom.
背後
前沿實驗室正由租用雲端算力,轉向直接承租機房與芯片,以繞開雲服務商的加價。交易仍需金融擔保與芯片融資,反映算力擴張已變成財務工程。Frontier labs are moving from renting cloud compute to leasing buildings and chips directly in order to bypass cloud mark-ups. The deal still needs financial guarantees and chip financing, showing that scaling compute has become a financing exercise.
顧問觀點

我們認為這條新聞的價值在於訂出參照。當 1 吉瓦等於至少 400 億美元,企業日後評估任何「AI 基建」報價時,就多了一個可以量度的錨。The value of this story is the reference price it sets. When a gigawatt equals at least $40 billion, any future AI infrastructure quote can be measured against a concrete anchor.

對日常工作的影響
資訊科技主管要為算力預算設定單位成本上限;財務與法務在簽署長期算力或雲端合約前,須確認退出條款與擔保責任。IT leaders should set a unit-cost ceiling for compute, and finance and legal must confirm exit terms and guarantee obligations before signing long-term compute or cloud contracts.
如何改善
本週把公司現有 AI 相關支出換算成每千次任務成本,作為日後議價與續約的基準。This week, convert your current AI spend into a cost per thousand tasks to serve as the baseline for future negotiations and renewals.

日本金融廳加強審查銀行對 AI 數據中心的融資Japan's FSA steps up scrutiny of bank financing for AI data centres

影響力6–12 個月6–12 months企業決策者Business owners資訊科技IT
事件
日本金融廳表示正加強審查該國大型銀行與壽險公司對 AI 數據中心的融資,包括放款機構的風險管理框架,並指涉及項目主要在美國。Japan's Financial Services Agency says it is stepping up scrutiny of AI data-centre financing by the country's largest banks and life insurers, including lenders' risk-management frameworks, noting most projects involved are in the United States.
背後
數據中心項目融資已被列入該廳本月公布的監察重點。監管機構關注的是超大規模雲商能否產生足夠回報,並非阻止放款,屬風險提示多於收緊。Data-centre project finance was named among the agency's monitoring priorities this month. The concern is whether hyperscalers can generate adequate returns rather than lending itself, making this a risk signal more than a tightening.
顧問觀點

我們認為亞洲監管機構開始把 AI 熱潮當作金融風險處理,而非單純科技議題。這意味企業的 AI 投資,日後會同時受技術與信貸兩套語言審視。Asian regulators are beginning to treat the AI boom as a financial risk rather than purely a technology story. Corporate AI investment will increasingly be read in the language of credit as well as technology.

對日常工作的影響
財務與資訊科技在規劃大型 AI 基建時,要準備可向銀行解釋的回報模型;上市公司董事會須把 AI 資本開支納入風險披露討論。Finance and IT planning large AI infrastructure must prepare a return model a bank can follow, and listed-company boards should bring AI capital expenditure into risk-disclosure discussions.
如何改善
本週為公司在談的每一項 AI 投資,補上一頁假設與回報推算,寫明最壞情況下的退出方式。This week, add a one-page set of assumptions and return estimates, including the exit route in the worst case, to every AI investment under discussion.

本週可做的三件事

  1. 為每一項已上線的 AI 工序寫下三行:每月成本上限、負責人姓名、停用條件。Add three lines to every AI process already live: a monthly cost ceiling, a named owner, and the condition that stops it.
  2. 列出公司所有自動篩選、評分與排序流程(包括用試算表做的),作為合規問卷的底稿。List every automated screening, scoring and ranking process in the company, spreadsheets included, as the first draft of your compliance answers.
  3. 為一個初級職位重寫職務說明,刪去已被工具取代的工序,補上一項由新人負責的判斷工作。Rewrite one junior job description: remove the steps a tool now performs, and add one judgement task that the newcomer owns.

常見問題

今日(2026-09-26)「AiX 環球 AI 情報」有哪十條重點?

今日十條為:1、Anthropic 與 OpenAI 同日減價,前沿模型 API 定價腰斬;2、美團發布 LongCat-2.5-Preview,1.6 兆參數主打長流程 Agent;3、小米開源 MiMo-V2.6-Pro 登頂,開放權重模型已佔 token 用量 56%;4、歐盟 AI 法案首輪合規巡查,聚焦招聘篩選與信貸評分;5、內地《人工智能安全治理框架 3.0》把智能體風險納入治理主線;6、上海金融監管局推十六項措施,探索大模型直接面客試點;7、香港人力推算:AI 令初級職位空缺較 2022 年少約六成;8、高盛:AI 帶動的招聘放緩集中於客服、軟件、顧問與廣告;9、Anthropic 洽租最高 1 吉瓦算力,單吉瓦資本投入至少 400 億美元;10、日本金融廳加強審查銀行對 AI 數據中心的融資。每條均附本會顧問觀點、對日常工作的影響與一項可即時執行的建議。

本會對今日 AI 局勢的整體判斷是甚麼?

今日十條的共同主線是:AI 的成本正在下降,責任卻在上升。前沿模型在四十八小時內連環減價,內地同日以 1.6 兆參數模型加入長任務競賽;另一邊廂,歐盟啟動首輪合規巡查,內地要求智能體安全可控貫穿全周期,日本監管機構開始審視數據中心融資,香港的人力推算則把入職階梯收窄寫成具體數字。我們認為,企業今年的分水嶺不在買哪一個模型,而在有沒有人為每一項已上線的 AI 工序簽名。

這些情報的資料來源是甚麼?如何核實?

本欄每日由 AIX Society 編輯部檢索公開資料後撰稿,每條新聞均附原始來源連結(本期包括:FrontierNews.ai、AI Briefing、HuggingNews、Sentient Foundation、FinScan、中國經濟網(今日頭條)、上海證券報・中國證券網、中國新聞網),並將事實與本會觀點分列。讀者可按來源連結自行核實。

訂閱每週電子報

每週一封:AI 轉型的實戰觀察、工具實測與案例拆解。

每週一封 · 可隨時取消 · 私隱聲明