月之暗面放出 Kimi K3.1 Pro，输入价格砍了 35%，声明级幻觉率压低 65%，承诺 11 月 4 日前开源完整权重。
我做 AI 培训和企业陪跑两年，带过 200 多个学员，自己写了十多年代码。拿学员案例库重算了一遍 API 账单——团队不敢放手铺 Agent 自动化，卡点就两个：怕 AI 满嘴跑火车砸交付，怕长文本 API 太贵顶不住。
本文拆解它在哪省钱、业务怎么接，文末附可直接抄的「派活验收清单」。
没换底座，为什么变强了
Unite.AI 10 月 24 日的报道讲得很清楚。
K3.1 Pro 底层还是混合专家架构（MoE），总参数 2.8 万亿没变。
每次处理依然只激活 16 个专家，也就是 1040 亿参数。
上下文窗口维持在 100 万 token。
就像一家拥有 896 名专家的三甲医院，每次只挑最对口的 16 个人会诊。
以前的 K3 像刚招进来的名校高材生，现在的 K3.1 Pro 是月之暗面砸了海量算力做联合强化学习、在沙箱里打磨出来的「坐诊主任」。
三组关键数据：输入降价 35%（降至 13 元人民币/百万 token）、幻觉减少 65%、模拟企业运营内部测试得分提升 4.2 倍。
跑分与业务能力
The Decoder 10 月 24 日的拆解显示，长程软件工程基准 SWE Marathon 上它拿了 51.7%，压过了 Claude Opus 5.5 的 46.3%。
终端操作基准 Terminal-Bench 4.0 上它拿到 65.7%，也赢了 GPT-6 Astra 的 58.2%。
业务端的变化更值得关注。
BenchCAD 工具测试它拿了 92.7% 的高分。
OfficeQA Pro v2 上以 64.4 分拿到 SOTA。
模拟企业运营的内部测试，从上一代的 8.9 分飙升到 37.0 分。
放到真实业务里，至少有三类重活可以分给它。
做硬件打样或工业零件的老板，在 Kimi 网页端或 App 里打开「3D Make」，改参数直接出 3D 打印文件。
电商财务算季度账与模拟排产，直接丢进 100 万 token 跨表文档。
它的金融建模内测分涨到了 57.6，金融研究涨到了 70.4。
技术团队做全项目开发，让它接手 Unreal、Unity 或内部脚本，长周期改 Bug 不再轻易失忆。
这三类活的共同点很明确：都有清晰的验收口径，但过程特别磨人。以前要么招人慢慢磨，要么不敢交给 AI。现在长链条能力上来了，加上降价，第一次出现「又快、又稳、又便宜」三样齐的组合。对预算有限的中小团队来说，这是比跑分更有感知的变化。
定价与缓存
OrcaRouter 和 AIML API 10 月 24 日的定价表写得很明白。
K3.1 Pro 的 API 输入价格降了 35%，每 100 万 token 只要 2 美元或 13 元人民币。
输出价格降了 32%，来到 10 美元每 100 万 token。
赶时间的话，官方还放出了快 2 到 3 倍的 Highspeed 版，输入 4 美元、输出 20 美元。
但最值得关注的是缓存输入价格。
两个版本都只要 0.20 美元每 100 万 token。
这跟给企业的长文档知识库开「宽带包月」没区别。
真不是 AI 越来越贵，而是你没把重复读的资料塞进 0.2 美元的缓存池里。
接入三步与暗坑
研究完官方文档，这里藏着几个极容易踩的坑。
参数只要填错一个字母，你花钱调用的其实还是老模型。
按下面三步走，先做最小闭环测试。
第一步，先升客户端和桌面端。
网页端打开 Kimi.ai 就行。
电脑办公的朋友记得把 Kimi Work 桌面端升到 3.1.0 以上，支持 Windows 和苹果芯片的 Mac。
写代码的在 Kimi Code 里直接敲这行命令换模型。
/model kimi-k3.1-pro
换完后必须另开新会话。
在老会话接着聊，根本激活不了新模型的完整推理能力。
第二步，核对第三方工具和 API 参数。
在代码编辑器或自动化流里接 API，模型 ID 必须一字不差。
kimi-k3.1-pro
kimi-k3.1-pro-highspeed
千万核对拼写！官方 10 月 24 日文档明确说了，第三方工具里 ID 一旦拼错，系统不会报错停机，而是默默回退到没思考模式的 K2.8 Preview。企业版找不到选项的话，直接找管理员在后台开权限。
第三步，给业务流程加上安全红线。
Kimi 内部测试显示，它的声明级幻觉率降到了 8.3%，错误回答降到了上一代的 42.4%。
为了防网络安全失控，月之暗面还删了相关训练数据，把漏洞利用测试 pass@3 压到 81.0%。
但 AI 再厉害也只是个「外部实习生」。
安全红线一步都不能退。
核心算法源码、客户身份证号与手机号、没脱敏的流水底价，坚决不能直接丢进网页端。
真要处理这些资产，必须走开启 ZDR 零数据保留协议的 API。
或者等 11 月 4 日前开源权重发布，让技术拉回本地内网部署。
一句话：宁可派活前花十分钟卡死安全红线，绝不交差后花十万块去堵泄密漏洞。
派活说明书
谁适合上车？
如果你只是拿 AI 写两百字朋友圈、查个菜谱，默认版完全够用。
但如果你靠批量产内容、频繁扒跨表研报，或者正嫌 Claude 太贵想找平替，它就是眼下极具性价比的主力选配。
照着这 3 个动作做就行。
今天下班前打开 Kimi Work 3.1.0 或网页端，点开「3D Make」或丢一份脱敏表格进去跑一次。
检查现有的脚本，把模型 ID 换成 kimi-k3.1-pro，顺手把固定资料推进 0.2 美元的缓存池。
复制下面这段提示词，当作派复杂任务的第一段指令。
【任务目标】请帮我完成（填入具体业务，如：基于附件脱敏财报生成Q4现金流预测表 / 生成可3D打印的卡扣支架参数模型）。
【边界与红线】本次输入已剔除客户隐私与核心底价；请严格基于我提供的100万token上下文资料作答，若资料中无明确依据，请直接标注「资料未提及」，严禁自行脑补编造数据。
【前置验收标准】
1. 交付物必须包含可执行的源码/可导出的参数文件，以及一份关键数字溯源表；
2. 每个结论后方需括号注明引用自哪份文档的第几页；
3. 输出前请自行核对一遍计算公式，若发现逻辑冲突请先向我提问，不要直接输出半成品。
门槛已经被砍掉三分之一了，剩下的就看你能不能狠下心把自家流程拆碎喂给它。
最后再压一遍今天的行动顺序：先换 ID、再开新会话验证、然后把重复读的固定资料推进缓存池、最后给所有派活指令加上验收标准。四件事都是十分钟以内的活，但每一件都直接决定你下个月的账单和交付质量。
本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
The dark side of the moon released Kimi K3.1 Pro, which cut the input price by 35 per cent, declared a low hallucinogenic rate of 65 per cent, and committed to full open source weight by 4 November.
I've done AI training and business running for two years, with over 200 trainees, writing their own code for over a decade. Recalculate the API bill with the student's casebook -- the team won't let go of Agent automating, and the card points are two: afraid of AI running the train, afraid of long text API being too expensive.
This paper breaks down where it saves money and how it does business.
Why are you getting stronger?
Unite.AI's coverage on October 24th was clear.
K3.1 Pro is also a hybrid specialist structure (MoE), with a total parameter of 2.8 trillion.
Only 16 experts, or 104 billion parameters, were activated each time they were processed.
context window maintains at 1 million token.
It's like a three-accelerator hospital with 896 specialists, with only 16 of the right people per visit.
The former K3 is like the recently recruited high school student, and the current K3.1 Pro is a "sitting director" in a sandbox after the dark side of the moon smashed into a mass calculus for intensive joint learning.
Three sets of key data: 35 per cent (down to 13 yuan/million token), 65 per cent reduction in hallucinations, 4.2 times increase in internal testing of simulated enterprises.
Running points and operational capabilities
The Decoder decomposition on October 24 shows that the long-range software engineering benchmark SWE Marathon took 51.7 per cent of it and overcrushed 46.3 per cent of Claude Opus 5.5.
The terminal operating benchmark Terminal-Bench 4.0 received 65.7 per cent and won 58.2 per cent of GPT-6 Astra.
Business-level changes are even more noteworthy.
The BenchCAD tool test took 92.7% of the high score.
OfficeQA Pro v2 got SOTA on 64.4.
Internal testing of the operation of simulated enterprises surged from the previous generation's 8.9 to 37.0.
In real business, at least three types of heavy work can be assigned to it.
The owner of the hardware sample or industrial parts opens "3D Make" on either the Kimi web page or the App, changing the parameter directly from the 3D print file.
Electricians run quarterly accounts and simulated discharges, which are thrown directly into 1 million token cross-table documents.
Its financial modelling has increased to 57.6 and financial research to 70.4.
The technical team develops the entire project so that it can take over the Unreal, Unity or internal scripts and change the Bugs over the long term.
The common denominator of these three types of work is clear: there is a clear acceptance check caliber, but the process is particularly difficult. It used to be either slow or afraid to give it to AI. For the first time, there is a combination of "quick, steady and cheap" with long chain capacity and lower prices. For small and medium-sized teams with limited budgets, this is a more perceived change than running points.
Pricing and cache
The pricing forms for OrcaRouter and AIML API on October 24 are clear.
K3.1 Pro's API input price dropped by 35 per cent for every 1 million tokens for only $2 or 13 yuan.
The output price dropped 32%, and came to $10 per million token.
In a hurry, the official release of the nearly 2-3 times the Highspeed version entered $4 and exported $20.
However, the price of cache input is of greatest concern.
Both versions only cost 0.20 dollars per million token.
This is no different from "broadband pack month" for the long-documented knowledge base of companies.
It's not AI that's getting more expensive, but you didn't put the double-reading in the $0.2 cache pool.
Access three steps to the pit.
After studying the official documents, there are a few very easy pits.
All you have to do is fill in the wrong letter. You're using the old model.
Three steps down, with a minimum closed circle test.
First step, go first to the client and desktop.
The page ends with Kimi.ai.
Computer office friends remember to raise Kimi Work desktops above 3.1.0 to support the Windows and Apple chips Mac.
The code writer in Kimi Code knocked directly on the line to change the model.
/model kimi-k3.1-pro
After that, a new session must be opened.
Moving on with the old conversation, there is no way to activate the full reasoning of the new model.
Step two, check third-party tools and API parameters.
API, model ID, must be identical.
kimi-k3.1-pro
kimi-k3.1-pro-highspeed
The official October 24 file makes it clear that the IDs in the third-party tool, if spelled wrong, do not miss the stop, but rather the silent rollback to K2.8 Preview without thinking. If the enterprise version does not find an option, contact the administrator to open permission in the backstage.
Step three, add a secure red line to business processes.
According to the Kimi internal test, the rate of its declarative hallucinogenicity fell to 8.3 per cent, while the wrong answer fell to 42.4 per cent of the previous generation.
Training data were also deleted from the dark side of the month in order to prevent network security from going out of control, and the gap was used to test pass@3 to pressure 81.0 per cent.
But AI is just an outside intern.
There's no turning back the red line.
Core algorithms, customer ID numbers and cell phone numbers, unsensitized bottom-up prices cannot be thrown directly into the web page.
If you really want to deal with these assets, you must go to the API that opens the ZDR zero data retention protocol.
Or wait until November 4th, open source weight publish, to get technology back to local intranet deployment.
In one sentence, it would be better to send a safe red line to die 10 minutes before it's alive, and not to pay $100,000 for the leak.
I'll give you the instructions.
Who's fit to get in?
If you're just taking AI to write a 200-word circle of friends and check a recipe, the default version is perfect.
But if you're looking at mass content, you're looking at it frequently, or you're thinking that Claude's too expensive to look for a replacement, it's the main choice for the right moment.
Just follow the three moves.
Opens Kimi Work 3.1.0 or a web page by the end of the day, clicks "3D Make" or drops a de-sensitization form and runs.
Check the existing script and replace the model ID with Kimi-k3.1-pro and move the fixed data to the $0.2 cache pool.
Copy the following prompt as the first instruction for a complex mission.
[Target objective], please help me with this (insert specific operations, such as generating Q4 cash flow projection tables based on the Annex De-Sensitization Financial Statements / Generating 3D-printable model of card button parameters).
This input has removed the client's privacy and core price; please answer strictly on the basis of the 1 million tokenZ context information I have provided, and if there is no clear basis for this information, indicate "the information is not mentioned" and strictly prohibit the use of self-inflicted supplements.
acceptance criteria
1. The deliverable shall contain an enforceable source code/exportable parameter file, as well as a key digital traceability table;
2. The page of the document from which the reference is made in brackets at the end of each conclusion;
3. Please check the formula yourself before the output, and if you find a logical conflict, ask me first not to directly export the semi-finished.
The threshold has been cut off by a third, and the rest depends on whether you can feed it with your own procedures.
Finally, the order of action for today's event will be changed, a new session will be held to verify, and then the regular information will be rereaded to the cache pool, and then acceptance criteria will be added to all the faction orders. Four things are within 10 minutes, but each one directly determines the quality of your bill and delivery next month.
Auto-fetched and translated by AI Atlas. All rights belong to the original author.