diff --git a/_additional_platforms/ascend_npu.json b/_additional_platforms/ascend_npu.json
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+{
+  "name": "Ascend NPU",
+  "support_channel": "https://github.com/Ascend/pytorch/issues",
+  "stable": {
+    "linux": "pip3 install torch torchvision && pip3 install torch-npu"
+  }
+}
diff --git a/_get_started/additional_platforms/ascend_npu.md b/_get_started/additional_platforms/ascend_npu.md
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+# Installing on Ascend NPU
+
+Ascend NPU is Huawei's AI processor series (including Ascend 910B, 910C, and 310P). The Ascend Extension for PyTorch (`torch_npu`) enables PyTorch to run on Ascend NPUs, supporting eager-mode execution, distributed training, and mixed precision via the `PrivateUse1` backend.
+
+## Prerequisites
+
+### Hardware Requirements
+
+* Ascend 910B, 910C, or 310P processor
+
+### Software Requirements
+
+* Python >= 3.10
+* CANN (Compute Architecture for Neural Networks) toolkit installed >= 8.0
+* Ascend driver and firmware installed
+
+Before installing PyTorch with Ascend NPU support, you must install the CANN toolkit. Download it from the [Ascend Community](https://www.hiascend.com/) and follow the [CANN Installation Guide](https://www.hiascend.com/cann/download?versionId=735&ids=d806%2Ch0501%2Ch0601%2Ch0702).
+
+## Installation
+
+### pip
+
+Use the pip package manager to install PyTorch with Ascend NPU support. Select your preferred options in the selector above to get the installation command.
+
+After installation, source the CANN environment:
+
+```bash
+source <ASCEND_INSTALL_DIR>/Ascend/cann/set_env.sh
+source <ASCEND_INSTALL_DIR>/Ascend/nnal/atb/set_env.sh
+```
+
+## Verification
+
+To ensure that PyTorch was installed correctly with Ascend NPU support, run the following code:
+
+```python
+import torch
+import torch_npu
+
+print(torch.__version__)
+print("torch_npu version:", torch_npu.__version__)
+
+if torch.npu.is_available():
+    print("Ascend NPU is available!")
+    print(f"NPU count: {torch_npu.npu.device_count()}")
+    print(f"NPU name: {torch_npu.npu.get_device_name(0)}")
+
+    # Test basic computation
+    a = torch.randn(3, 4).npu()
+    b = torch.randn(3, 4).npu()
+    print("NPU computation result:", a + b)
+else:
+    print("Ascend NPU is not available.")
+```
+
+Expected output should show the PyTorch and torch_npu versions, NPU count, device name, and the result of a tensor addition without errors.
+
+## Documentation
+
+For more information, please visit:
+
+* [Ascend Extension for PyTorch Official Documentation](https://www.hiascend.com/document/detail/zh/Pytorch/2600/index/index.html)
+* [Ascend Community Portal](https://www.hiascend.com/)
+* [Ascend/pytorch GitHub Repository](https://github.com/Ascend/pytorch)
+* [PyPI: torch-npu](https://pypi.org/project/torch-npu/)