From 5a434b5b50a171fd39a18f43edd0d372be1e7482 Mon Sep 17 00:00:00 2001
From: cal-weng <wenghao@bytetrade.io>
Date: Sat, 11 Oct 2025 21:45:15 +0800
Subject: [PATCH] resolve comments

---
 docs/manual/olares/settings/gpu-resource.md   | 20 +++++++++---------
 .../zh/manual/olares/settings/gpu-resource.md | 21 +++++++++----------
 2 files changed, 20 insertions(+), 21 deletions(-)

diff --git a/docs/manual/olares/settings/gpu-resource.md b/docs/manual/olares/settings/gpu-resource.md
index b448dcd9d..3076eaaeb 100644
--- a/docs/manual/olares/settings/gpu-resource.md
+++ b/docs/manual/olares/settings/gpu-resource.md
@@ -27,23 +27,23 @@ Even if your GPU architecture is supported, **low VRAM capacity may cause AI app
 
 Olares supports three GPU allocation modes. Choosing the right mode helps optimize performance based on your needs.
 
-### Time Slicing 
-
-In this mode, the GPU rotates across applications in time slices.
-- At any instant, only one application uses the GPU’s compute and VRAM.
-- Other applications’ VRAM contents are temporarily swapped out to system memory.
-- Applications not assigned an exclusive GPU or dedicated VRAM are placed in the time-slicing queue by default.
-
 ### App Exclusive
 
 In this mode, the GPU’s full compute capacity and VRAM are allocated to a single application to ensure the maximized performance.
 
 ### Memory Slicing
 
-In this mode, GPU VRAM is allocated to multiple applications by specified quotas:
+In this mode, GPU VRAM is allocated to multiple applications by specified VRAM quotas:
 
-- Applications with a quota can run concurrently on the GPU.
-- The sum of all quotas must not exceed the GPU’s physical VRAM.
+- Applications with assigned VRAM can run concurrently on the GPU.
+- The sum of all assigned VRAMs must not exceed the GPU’s physical VRAM.
+
+### Time Slicing
+
+In this mode, any number of applications can be bound to the same GPU:
+
+- At any instant, only one application fully occupies the GPU’s compute and VRAM.
+- VRAM contents of other applications are temporarily swapped out to system memory.
 
 ## View GPU status
 
diff --git a/docs/zh/manual/olares/settings/gpu-resource.md b/docs/zh/manual/olares/settings/gpu-resource.md
index afdd5d410..010d9df45 100644
--- a/docs/zh/manual/olares/settings/gpu-resource.md
+++ b/docs/zh/manual/olares/settings/gpu-resource.md
@@ -28,22 +28,21 @@ Olares 仅支持 **NVIDIA 显卡**，且要求架构为 **Turing 或更新**（T
 
 Olares 提供三种分配方式，可按场景灵活选择。
 
-### 时间分片模式
-
-在此模式下，多应用按时间片轮转共享同一 GPU：
-- 任一时刻仅有一个应用占用 GPU 算力和显存。
-- 此时其他应用的显存内容会暂时换出至系统内存。 
-- 未被分配独占 GPU 或专有显存的应用将默认加入时间分片队列。
-
 ### 应用独占模式
 
-在此模式下，整个 GPU 的算力和显存将分配给单个应用，以保证最佳性能。
+在此模式下，单张 GPU 的算力和显存将分配给一个应用，以保证最佳性能。
 
 ### 显存分片模式
 
-在此模式下，GPU 显存可按指定配额分配给多个应用。
-- 获得配额的应用可并行使用 GPU。
-- 所分配配额之和不得超过总物理显存。
+在此模式下，GPU 显存可按指定显存分配给多个应用。
+- 所有获得显存的应用可同时使用 GPU。
+- 所分配显存之和不得超过总物理显存。
+
+### 时间分片模式
+
+在此模式下，任意数量应用可绑定至同一 GPU：
+- 任一时刻仅有一个应用完全占用 GPU 算力和显存。
+- 此时其他应用的显存内容会暂时换出至系统内存。
 
 ## 查看显卡状态