diff --git a/docs/index.md b/docs/index.md
index 72adfc3..9e449e0 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -107,6 +107,26 @@ were pre-registered, and one of them is falsified. The numbers, the recorded
 environment of both processes, and what none of it supports:
 [E11](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e11-vla-rl-libero).
 
+## The environment side needs neither CUDA nor a GPU
+
+The training server is 6.5G and wants a GPU. The machine running environments
+does not have to be either. A LIBERO env client installs at **3.4G with no
+nvidia wheels** instead of 7.8G with sixteen, sending byte-identical
+observations, and renders on the **CPU** - ten clients at once, 30 of 30
+episodes successful, at **1.91x** the wall clock of the same run on a GPU.
+
+The catch is that 1.91x, and the numbers that make it: stepping is 10x slower
+in software, and most but not all of that hides behind the queue of clients
+waiting on one policy.
+
+This overturns a conclusion the project had already published. E1 measured a
+robomimic-class env client at 7.2G with CUDA and said the environment side does
+need a GPU; that was true of a default install, where `torch` brings CUDA along
+whether or not anything uses it. [E12](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e12-cuda-free-rollout)
+reproduced E1's row exactly before changing one pin, and
+[E13](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e13-gpu-free-rendering)
+measured what rendering without a GPU costs.
+
 ## Components
 
 - `plugrl-server`: training server, runs algorithm, policy, checkpoints, tracking
diff --git a/docs/index.zh.md b/docs/index.zh.md
index 1f5baf7..1947aed 100644
--- a/docs/index.zh.md
+++ b/docs/index.zh.md
@@ -94,6 +94,22 @@ FPO 用回传的反馈训练。边界本身没有任何改动，变的只是策
 进程各自被记录下来的环境，以及这些数据**不能**支持的结论，见
 [E11](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e11-vla-rl-libero)。
 
+## 环境端既不需要 CUDA，也不需要 GPU
+
+训练端有 6.5G，而且要一张显卡；跑环境的那台机器不必如此。LIBERO 环境端可以装成
+**3.4G、零个 nvidia wheel**（原本是 7.8G 带十六个），发出的观测逐字节相同，并且能在
+**CPU 上渲染**——十个客户端同时跑，30 个回合全部成功，代价是 **1.91 倍**墙钟。
+
+代价就在这 1.91 倍上，构成它的数字是：软件渲染的单步慢 10 倍，其中大部分、但不是
+全部，被"多个客户端排队等同一个策略"的等待所掩盖。
+
+这推翻了本项目自己已经写下的结论。E1 曾测得 robomimic 类环境端 7.2G 且带 CUDA，并
+断言这类环境的环境端**确实**需要 GPU——那对**默认安装**是成立的，因为 Linux 上
+`torch` 无论用不用都会把 CUDA 一起带来。[E12](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e12-cuda-free-rollout)
+先原样复现了 E1 那一行，再只改一个版本钉定；
+[E13](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e13-gpu-free-rendering)
+则量出了无 GPU 渲染的代价。
+
 ## 组件
 
 - `plugrl-server`：训练端，负责算法、策略、checkpoint、指标追踪