Dan Luu 写系统问题时，习惯先测量、再对照、最后才下结论。把「Computer latency: 1977-2017」放到智能体、评测和线上系统里，真正要问的是：默认做法会不会系统性失败。下面用中文整理成可执行的工程笔记，去掉原站导航和无关链接。

Why is the apple 2e so fast?

I've had this nagging feeling that the computers I use today feel slower than the computers I used as a kid. As a rule, I don’t trust this kind of feeling because human perception has been shown to be unreliable in empirical studies, so I carried around a high-speed camera and measured the response latency of devices I’ve run into in the past few months. Here are the results:

These are tests of the latency between a keypress and the display of a character in a terminal (see appendix for more details). The results are sorted from quickest to slowest. In the latency column, the background goes from green to yellow to red to black as devices get slower and the background gets darker as devices get slower. No devices are green. When multiple OSes were tested on the same machine, the os is in bold . When multiple refresh rates were

iOS rendering pipeline

In the year column, the background gets darker and purple-er as devices get older. If older devices were slower, we’d see the year column get darker as we read down the chart.

The next two columns show the clock speed and number of transistors in the processor. Smaller numbers are darker and blue-er. As above, if slower clocked and smaller chips correlated with longer latency, the columns would get darker as we go down the table, but it, if anything, seems to be the other way around.

Refresh rate vs. latency

For reference, the latency of a packet going around the world through fiber from NYC back to NYC via Tokyo and London is inserted in the table.

If we look at overall results, the fastest machines are ancient. Newer machines are all over the place. Fancy gaming rigs with unusually high refresh-rate displays are almost competitive with machines from the late 70s and early 80s, but “normal” modern computers can’t compete with thirty to forty year old machines.

Complexity

We can also look at mobile devices. In this case, we’ll look at scroll latency in the browser:

As above, the results are sorted by latency and color-coded from green to yellow to red to black as devices get slower. Also as above, the year gets purple-er (and darker) as the device gets older.

Conclusion

If we exclude the game boy color , which is a different class of device than the rest, all of the quickest devices are Apple phones or tablets. The next quickest device is the blackberry q10 . Although we don’t have enough data to really tell why the blackberry q10 is unusually quick for a non-Apple device, one plausible guess is that it’s helped by having actual buttons, which are easier to implement with low latency than a touchscreen. The other two devi

After that iphones and non-kindle button devices, we have a variety of Android devices of various ages. At the bottom, we have the ancient palm pilot 1000 followed by the kindles. The palm is hamstrung by a touchscreen and display created in an era with much slower touchscreen technology and the kindles use e-ink displays, which are much slower than the displays used on modern phones, so it’s not surprising to see those devices at the bottom.

Other posts on latency measurement

Compared to a modern computer that’s not the latest ipad pro , the apple 2 has significant advantages on both the input and the output, and it also has an advantage between the input and the output for all but the most carefully written code since the apple 2 doesn’t have to deal with context switches, buffers involved in handoffs between different processes, etc.

On the input, if we look at modern keyboards, it’s common to see them scan their inputs at 100 Hz to 200 Hz (e.g., the ergodox claims to scan at 167 Hz ). By comparison, the apple 2e effectively scans at 556 Hz . See appendix for details.

值得单独记下的观察

• hardware has its own scanrate (e.g. 120 Hz for recent touch panels), so that can introduce up to 8 ms latency
• events are delivered to the kernel through firmware; this is relatively quick but system scheduling concerns may introduce a couple ms here
• the kernel delivers those events to privileged subscribers (here, backboardd ) over a mach port; more scheduling loss possible
• backboardd must determine which process should receive the event; this requires taking a lock against the window server, which shares that information (a trip back into the kernel, more scheduling delay)
• backboardd sends that event to the process in question; more scheduling delay possible before it is processed
• those events are only dequeued on the main thread; something else may be happening on the main thread (e.g. as result of a timer or network activity), so some more latency may result, depending on that work
• UIKit introduced 1-2 ms event processing overhead, CPU-bound
• (trivial changes are things which the render server can incorporate itself, like affine transformation changes or color changes to layers; non-trivial changes include anything that has to do with text, most raster and ve

落地时建议先做的 5 件事

1. 用自己的真实负载测，而不是只用公开榜或厂商数字。
2. 把评测设计成能抓到失败模式：平均分好看但尾部崩溃，仍然算失败。
3. 智能体默认不会好好用测试；要写进流程，而不是写在口头规范里。
4. 性能和正确性都要有基线，改模型或改语言前后必须能对比。
5. 结论写成可回滚的决策：哪一版配置、哪一版评测集、谁签字。

和智能体产品怎么接

龙虾PRO做 OpenClaw 落地时，同样吃「先测量再扩面」这条纪律：技能、数字员工和网关都要有可复现评测，而不是只看一次演示通过。

本文侧重全链路风控方法论。落地时请用自身业务单据做回放验证，不要把示例阈值直接当生产策略。 相关：风控体检 · 方案资源