diff --git a/docs/readthedocs/source/_toc.yml b/docs/readthedocs/source/_toc.yml
index b4c659c37db..d1dcbb2b061 100644
--- a/docs/readthedocs/source/_toc.yml
+++ b/docs/readthedocs/source/_toc.yml
@@ -51,6 +51,7 @@ subtrees:
                     - entries:
                       - file: doc/LLM/Overview/KeyFeatures/inference_on_gpu
                       - file: doc/LLM/Overview/KeyFeatures/finetune
+                      - file: doc/LLM/Overview/KeyFeatures/multi_gpus_selection
           - file: doc/LLM/Overview/examples
             title: "Examples"
             subtrees:
diff --git a/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/gpu_supports.rst b/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/gpu_supports.rst
index af0e6e6a09f..4d908c13da3 100644
--- a/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/gpu_supports.rst
+++ b/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/gpu_supports.rst
@@ -5,6 +5,10 @@ BigDL-LLM not only supports running large language models for inference, but als
 
 * |inference_on_gpu|_
 * `Finetune (QLoRA) <./finetune.html>`_
+* `Multi GPUs selection <./multi_gpus_selection.html>`_
 
 .. |inference_on_gpu| replace:: Inference on GPU
 .. _inference_on_gpu: ./inference_on_gpu.html
+
+.. |multi_gpus_selection| replace:: Multi GPUs selection
+.. _multi_gpus_selection: ./multi_gpus_selection.html
diff --git a/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/index.rst b/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/index.rst
index 94eb680622e..62891dfae86 100644
--- a/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/index.rst
+++ b/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/index.rst
@@ -14,6 +14,8 @@ You may run the LLMs using ``bigdl-llm`` through one of the following APIs:
 
   * |inference_on_gpu|_
   * `Finetune (QLoRA) <./finetune.html>`_
+  * `Multi GPUs selection <./multi_gpus_selection.html>`_
+
 
 .. |transformers_style_api| replace:: ``transformers``-style API
 .. _transformers_style_api: ./transformers_style_api.html
@@ -26,3 +28,6 @@ You may run the LLMs using ``bigdl-llm`` through one of the following APIs:
 
 .. |inference_on_gpu| replace:: Inference on GPU
 .. _inference_on_gpu: ./inference_on_gpu.html
+
+.. |multi_gpus_selection| replace:: Multi GPUs selection
+.. _multi_gpus_selection: ./multi_gpus_selection.html
diff --git a/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/multi_gpus_selection.md b/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/multi_gpus_selection.md
new file mode 100644
index 00000000000..3eb48769474
--- /dev/null
+++ b/docs/readthedocs/source/doc/LLM/Overview/KeyFeatures/multi_gpus_selection.md
@@ -0,0 +1,51 @@
+# Multi Intel GPUs selection
+
+In [Inference on GPU](inference_on_gpu.md) and [Finetune (QLoRA)](finetune.md), you have known how to run inference and finetune on Intel GPUs. In this section, we will show you two approaches to select GPU devices.
+
+## List devices
+
+The `sycl-ls` tool enumerates a list of devices available in the system. You can use it after you setup oneapi environment:
+```bash
+source /opt/intel/oneapi/setvars.sh
+sycl-ls
+```
+If you have two Arc770 GPUs, you can get something like below:
+```
+[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device 1.2 [2023.16.7.0.21_160000]
+[opencl:cpu:1] Intel(R) OpenCL, Intel(R) Core(TM) i9-14900K 3.0 [2023.16.7.0.21_160000]
+[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics 3.0 [23.17.26241.33]
+[opencl:gpu:3] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics 3.0 [23.17.26241.33]
+[opencl:gpu:4] Intel(R) OpenCL Graphics, Intel(R) UHD Graphics 770 3.0 [23.17.26241.33]
+[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26241]
+[ext_oneapi_level_zero:gpu:1] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26241]
+[ext_oneapi_level_zero:gpu:2] Intel(R) Level-Zero, Intel(R) UHD Graphics 770 1.3 [1.3.26241]
+```
+This output shows there are two Arc A770 GPUs on this machine.
+
+## Devices selection
+To enable xpu, you should convert your model and input to xpu by below code:
+```
+model = model.to('xpu')
+input_ids = tokenizer.encode(prompt, return_tensors="pt").to('xpu')
+```
+To select the desired devices, there are two ways: one is changing the code, another is adding an environment variable. See:  
+
+### 1. Select device in python
+To specify a xpu, you can change the `to('xpu')` to `to('xpu:[device_id]')`, this device_id is counted from zero.  
+If you you want to use the second device, you can change the code like this: 
+```
+model = model.to('xpu:1')
+input_ids = tokenizer.encode(prompt, return_tensors="pt").to('xpu:1')
+```
+
+### 2. OneAPI device selector
+Device selection environment variable, `ONEAPI_DEVICE_SELECTOR`, can be used to limit the choice of Intel GPU devices. As upon `sycl-ls` shows, the last three lines are three Level Zero GPU devices. So we can use `ONEAPI_DEVICE_SELECTOR=level_zero:[gpu_id]` to select devices.
+For example, you want to use the second A770 GPU, you can run the python like this:
+```
+ONEAPI_DEVICE_SELECTOR=level_zero:1 python generate.py
+```
+`ONEAPI_DEVICE_SELECTOR=level_zero:1` in upon command only affect in current python program. Also, you can export the environment, then run your python:
+```
+export ONEAPI_DEVICE_SELECTOR=level_zero:1
+python generate.py
+```