diff --git a/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.md b/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.md
index 1968d7dc..2c4be742 100644
--- a/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.md
+++ b/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.md
@@ -107,7 +107,7 @@ You could then use Ollama to run LLMs on Intel GPUs as follows:
 
 Ollama by default downloads model from the Ollama library. By setting the environment variable `IPEX_LLM_MODEL_SOURCE` to `modelscope` or `ollama` **before running Ollama**, you could switch the source where the model is downloaded.
 
-For example, if you would like to run `deepseek-r1:7b` but the download speed from the Ollama library is slow, you could download the model from [ModelScope](https://www.modelscope.cn/models) as follows:
+For example, if you would like to run `deepseek-r1:7b` but the download speed from the Ollama library is slow, you could download the model from ModelScope as follows:
 
 - For **Windows** users:
 
@@ -133,7 +133,7 @@ For example, if you would like to run `deepseek-r1:7b` but the download speed fr
 
 By default, Ollama runs model with a context window of 2048 tokens. That is, the model can "remember" at most 2048 tokens of context.
 
-To increase the context length, you could set environment variable `IPEX_LLM_NUM_CTX` **before Start Ollama Serve**, as shwon below (if Ollama serve is already running, please make sure to stop it first):
+To increase the context length, you could set environment variable `IPEX_LLM_NUM_CTX` **before staring Ollama Serve**, as shwon below (if Ollama serve is already running, please make sure to stop it first):
 
 - For **Windows** users:
 
@@ -154,7 +154,7 @@ To increase the context length, you could set environment variable `IPEX_LLM_NUM
 
 If your machine has multiple Intel GPUs, Ollama will by default runs on all of them.
 
-To specify which Intel GPU you would like Ollama to use, you could set environment variable `ONEAPI_DEVICE_SELECTOR` **before Start Ollama Serve**, as follows (if Ollama serve is already running, please make sure to stop it first):
+To specify which Intel GPU you would like Ollama to use, you could set environment variable `ONEAPI_DEVICE_SELECTOR` **before starting Ollama Serve**, as follows (if Ollama serve is already running, please make sure to stop it first):
 
 - Identify the id (e.g. 0, 1, etc.) for your multiple GPUs. You could find them in the logs of Ollama serve when loading any models, e.g.:
 
@@ -178,13 +178,13 @@ To specify which Intel GPU you would like Ollama to use, you could set environme
 
 The currently Ollama Portable Zip is based on Ollama v0.5.4; in addition, the following new models have also been supported in the Ollama Portable Zip:
 
-  | Model  | Download (Windows) | Download (Linux) | Model Link |
-  | - | - | - | - |
-  | DeepSeek-R1 | `ollama run deepseek-r1` | `./ollama run deepseek-r1` | [deepseek-r1](https://ollama.com/library/deepseek-r1) |
-  | Openthinker | `ollama run openthinker` | `./ollama run openthinker` | [openthinker](https://ollama.com/library/openthinker) |
-  | DeepScaleR | `ollama run deepscaler` | `./ollama run deepscaler` | [deepscaler](https://ollama.com/library/deepscaler) |
-  | Phi-4 | `ollama run phi4` | `./ollama run phi4` | [phi4](https://ollama.com/library/phi4) |
-  | Dolphin 3.0 | `ollama run dolphin3` | `./ollama run dolphin3` | [dolphin3](https://ollama.com/library/dolphin3) |
-  | Smallthinker | `ollama run smallthinker` |`./ollama run smallthinker` | [smallthinker](https://ollama.com/library/smallthinker) |
-  | Granite3.1-Dense |  `ollama run granite3-dense` | `./ollama run granite3-dense` | [granite3.1-dense](https://ollama.com/library/granite3.1-dense) |
-  | Granite3.1-Moe-3B | `ollama run granite3-moe` | `./ollama run granite3-moe` | [granite3.1-moe](https://ollama.com/library/granite3.1-moe) |
+| Model  | Download (Windows) | Download (Linux) | Model Link |
+| - | - | - | - |
+| DeepSeek-R1 | `ollama run deepseek-r1` | `./ollama run deepseek-r1` | [deepseek-r1](https://ollama.com/library/deepseek-r1) |
+| Openthinker | `ollama run openthinker` | `./ollama run openthinker` | [openthinker](https://ollama.com/library/openthinker) |
+| DeepScaleR | `ollama run deepscaler` | `./ollama run deepscaler` | [deepscaler](https://ollama.com/library/deepscaler) |
+| Phi-4 | `ollama run phi4` | `./ollama run phi4` | [phi4](https://ollama.com/library/phi4) |
+| Dolphin 3.0 | `ollama run dolphin3` | `./ollama run dolphin3` | [dolphin3](https://ollama.com/library/dolphin3) |
+| Smallthinker | `ollama run smallthinker` |`./ollama run smallthinker` | [smallthinker](https://ollama.com/library/smallthinker) |
+| Granite3.1-Dense |  `ollama run granite3-dense` | `./ollama run granite3-dense` | [granite3.1-dense](https://ollama.com/library/granite3.1-dense) |
+| Granite3.1-Moe-3B | `ollama run granite3-moe` | `./ollama run granite3-moe` | [granite3.1-moe](https://ollama.com/library/granite3.1-moe) |
diff --git a/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.zh-CN.md b/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.zh-CN.md
index d1cb98cf..8af0f0ec 100644
--- a/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.zh-CN.md
+++ b/docs/mddocs/Quickstart/ollama_portablze_zip_quickstart.zh-CN.md
@@ -19,6 +19,7 @@
 - [提示和故障排除](#提示和故障排除)
   - [通过切换源提升模型下载速度](#通过切换源提升模型下载速度)
   - [在 Ollama 中增加上下文长度](#在-ollama-中增加上下文长度)
+  - [在多块 GPU 可用时选择特定的 GPU 来运行 Ollama](#在多块-gpu-可用时选择特定的-gpu-来运行-ollama)
   - [Ollama v0.5.4 之后新增模型支持](#ollama-v054-之后新增模型支持)
 - [更多信息](ollama_quickstart.zh-CN.md)
 
@@ -61,9 +62,7 @@
 
 ### 系统环境准备
 
-检查你的 GPU 驱动程序版本，并根据需要进行更新：
-
-- 对于消费级显卡用户，如A系列，B系列和集成显卡，我们推荐按照[消费级显卡驱动安装指南](https://dgpu-docs.intel.com/driver/client/overview.html)来安装您的显卡驱动。
+检查你的 GPU 驱动程序版本，并根据需要进行更新；我们推荐用户按照[消费级显卡驱动安装指南](https://dgpu-docs.intel.com/driver/client/overview.html)来安装 GPU 驱动。
 
 
 ### 步骤 1：下载和解压
@@ -80,7 +79,6 @@ tar xvf [Downloaded tgz file]
 
 进入解压后的文件夹，执行`./start-ollama.sh`启动 Ollama Serve： 
 
-[可选操作] 对于有多块显卡的用户，请编辑解压后文件夹中的 start-ollama.sh，并根据机器配置修改 ONEAPI_DEVICE_SELECTOR。默认情况下，Ollama 会使用所有显卡。
 ```bash
  cd PATH/TO/EXTRACTED/FOLDER
 ./start-ollama.sh
@@ -105,13 +103,21 @@ tar xvf [Downloaded tgz file]
 
 ### 通过切换源提升模型下载速度
 
-Ollama 默认从 Ollama 库下载模型。通过在运行 Ollama 之前设置环境变量 `IPEX_LLM_MODEL_SOURCE` 为 `modelscope`或`ollama`，你可以切换模型的首选下载源。
+Ollama 默认从 Ollama 库下载模型。通过在**运行 Ollama 之前**设置环境变量 `IPEX_LLM_MODEL_SOURCE` 为 `modelscope` 或 `ollama`，你可以切换模型的下载源。
 
 例如，如果你想运行 `deepseek-r1:7b` 但从 Ollama 库的下载速度较慢，可以通过如下方式改用 ModelScope 上的模型源：
 
-- 打开命令提示符（cmd），并通过 `cd /d PATH\TO\EXTRACTED\FOLDER` 命令进入解压后的文件夹
-- 在命令提示符中运行 `set IPEX_LLM_MODEL_SOURCE=modelscope`
-- 运行 `ollama run deepseek-r1:7b`
+- 对于 **Windows** 用户：
+
+  - 打开命令提示符（cmd），并通过 `cd /d PATH\TO\EXTRACTED\FOLDER` 命令进入解压后的文件夹
+  - 在命令提示符中运行 `set IPEX_LLM_MODEL_SOURCE=modelscope`
+  - 运行 `ollama run deepseek-r1:7b`
+
+- 对于 **Linux** 用户：
+
+  - 在另一个终端（不同于运行 Ollama serve 的终端）中，输入指令 `cd PATH/TO/EXTRACTED/FOLDER` 进入解压后的文件夹
+  - 在终端中运行 `export IPEX_LLM_MODEL_SOURCE=modelscope`
+  - 运行 `./ollama run deepseek-r1:7b`
 
 > [!Tip]
 > 使用 `set IPEX_LLM_MODEL_SOURCE=modelscope` 下载的模型，在执行 `ollama list` 时仍会显示实际的模型 ID，例如：
@@ -125,26 +131,58 @@ Ollama 默认从 Ollama 库下载模型。通过在运行 Ollama 之前设置环
 
 默认情况下，Ollama 使用 2048 个 token 的上下文窗口运行模型。也就是说，模型最多能 “记住” 2048 个 token 的上下文。
 
-要增加上下文长度，可以在 [启动 Ollama serve](#步骤-2启动-ollama-serve) 之前设置环境变量 `IPEX_LLM_NUM_CTX`，步骤如下：
+要增加上下文长度，可以在**启动 Ollama serve 之前**设置环境变量 `IPEX_LLM_NUM_CTX`，步骤如下（如果 Ollama serve 已经在运行，请确保先将其停止）：
 
-- 打开命令提示符（cmd），并通过 `cd /d PATH\TO\EXTRACTED\FOLDER` 命令进入解压后的文件夹
-- 在命令提示符中将 `IPEX_LLM_NUM_CTX` 设置为所需长度，例如：`set IPEX_LLM_NUM_CTX=16384`
-- 通过运行 `start-ollama.bat` 启动 Ollama serve
+- 对于 **Windows** 用户：
+
+  - 打开命令提示符（cmd），并通过 `cd /d PATH\TO\EXTRACTED\FOLDER` 命令进入解压后的文件夹
+  - 在命令提示符中将 `IPEX_LLM_NUM_CTX` 设置为所需长度，例如：`set IPEX_LLM_NUM_CTX=16384`
+  - 通过运行 `start-ollama.bat` 启动 Ollama serve
+
+- 对于 **Linux** 用户：
+
+  - 在终端中输入指令 `cd PATH/TO/EXTRACTED/FOLDER` 进入解压后的文件夹
+  - 在终端中将 `IPEX_LLM_NUM_CTX` 设置为所需长度，例如：`export IPEX_LLM_NUM_CTX=16384`
+  - 通过运行 `./start-ollama.sh` 启动 Ollama serve
 
 > [!Tip]
 > `IPEX_LLM_NUM_CTX` 的优先级高于模型 `Modelfile` 中设置的 `num_ctx`。
 
+### 在多块 GPU 可用时选择特定的 GPU 来运行 Ollama
+
+如果你的机器上有多块 GPU，Ollama 默认会在所有 GPU 上运行。
+
+你可以通过在**启动 Ollama serve 之前**设置环境变量 `ONEAPI_DEVICE_SELECTOR` 来指定在特定的 Intel GPU 上运行 Ollama，步骤如下（如果 Ollama serve 已经在运行，请确保先将其停止）：
+
+- 确认多块 GPU 对应的 id (例如0，1等)。你可以通过在加载任何模型时查看 Ollama serve 的日志来找到它们，例如：
+
+  <div align="center">
+    <img src="https://llm-assets.readthedocs.io/en/latest/_images/ollama_portable_multi_gpus.png"  width=80%/>
+  </div>
+
+- 对于 **Windows** 用户：
+
+  - 打开命令提示符（cmd），并通过 `cd /d PATH\TO\EXTRACTED\FOLDER` 命令进入解压后的文件夹
+  - 在命令提示符中设置 `ONEAPI_DEVICE_SELECTOR` 来定义你想使用的 Intel GPU，例如 `set ONEAPI_DEVICE_SELECTOR=level_zero:0`，其中`0`应该替换成你期望的 GPU id
+  - 通过运行 `start-ollama.bat` 启动 Ollama serve
+
+- 对于 **Linux** 用户：
+
+  - 在终端中输入指令 `cd PATH/TO/EXTRACTED/FOLDER` 进入解压后的文件夹
+  - 在终端中设置 `ONEAPI_DEVICE_SELECTOR` 来定义你想使用的 Intel GPU，例如 `export ONEAPI_DEVICE_SELECTOR=level_zero:0`，其中`0`应该替换成你期望的 GPU id
+  - 通过运行 `./start-ollama.sh` 启动 Ollama serve
+
 ### Ollama v0.5.4 之后新增模型支持
 
 当前的 Ollama Portable Zip 基于 Ollama v0.5.4；此外，以下新模型也已在 Ollama Portable Zip 中得到支持：
 
-  | 模型  | 下载 | 模型链接 |
-  | - | - | - |
-  | DeepSeek-R1 | `ollama run deepseek-r1` | [deepseek-r1](https://ollama.com/library/deepseek-r1) |
-  | Openthinker | `ollama run openthinker` | [openthinker](https://ollama.com/library/openthinker) |
-  | DeepScaleR | `ollama run deepscaler` | [deepscaler](https://ollama.com/library/deepscaler) |
-  | Phi-4 | `ollama run phi4` | [phi4](https://ollama.com/library/phi4) |
-  | Dolphin 3.0 | `ollama run dolphin3` | [dolphin3](https://ollama.com/library/dolphin3) |
-  | Smallthinker | `ollama run smallthinker` | [smallthinker](https://ollama.com/library/smallthinker) |
-  | Granite3.1-Dense |  `ollama run granite3-dense` | [granite3.1-dense](https://ollama.com/library/granite3.1-dense) |
-  | Granite3.1-Moe-3B | `ollama run granite3-moe` | [granite3.1-moe](https://ollama.com/library/granite3.1-moe) |
+| 模型  | 下载（Windows）| 下载（Linux）| 模型链接 |
+| - | - | - | - |
+| DeepSeek-R1 | `ollama run deepseek-r1` | `./ollama run deepseek-r1` | [deepseek-r1](https://ollama.com/library/deepseek-r1) |
+| Openthinker | `ollama run openthinker` | `./ollama run openthinker` | [openthinker](https://ollama.com/library/openthinker) |
+| DeepScaleR | `ollama run deepscaler` | `./ollama run deepscaler` | [deepscaler](https://ollama.com/library/deepscaler) |
+| Phi-4 | `ollama run phi4` | `./ollama run phi4` | [phi4](https://ollama.com/library/phi4) |
+| Dolphin 3.0 | `ollama run dolphin3` | `./ollama run dolphin3` | [dolphin3](https://ollama.com/library/dolphin3) |
+| Smallthinker | `ollama run smallthinker` |`./ollama run smallthinker` | [smallthinker](https://ollama.com/library/smallthinker) |
+| Granite3.1-Dense |  `ollama run granite3-dense` | `./ollama run granite3-dense` | [granite3.1-dense](https://ollama.com/library/granite3.1-dense) |
+| Granite3.1-Moe-3B | `ollama run granite3-moe` | `./ollama run granite3-moe` | [granite3.1-moe](https://ollama.com/library/granite3.1-moe) |