diff --git a/llm/android/LlamaDemo/docs/delegates/qualcomm_README.md b/llm/android/LlamaDemo/docs/delegates/qualcomm_README.md
index e2e47521..e6471692 100644
--- a/llm/android/LlamaDemo/docs/delegates/qualcomm_README.md
+++ b/llm/android/LlamaDemo/docs/delegates/qualcomm_README.md
@@ -6,13 +6,13 @@ More specifically, it covers:
 2. Building and linking libraries that are required to inference on-device for Android platform using Qualcomm AI accelerators.
 3. Building the Android demo app itself.
 
-Verified on Linux CentOS, QNN SDK [v2.26](https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.26.0.240828.zip), python 3.10, Android SDK r27b.
+Verified on Linux CentOS, QNN SDK [v2.26](https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.26.0.240828.zip), python 3.10, Android NDK r27b.
 
 Phone verified: OnePlus 12, Samsung 24+, Samsung 23
 
 ## Prerequisites
 * Download and unzip QNN SDK [v2.26](https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.26.0.240828.zip)
-* Download and unzip Android SDK [r27b](https://developer.android.com/ndk/downloads)
+* Download and unzip Android NDK [r27b](https://developer.android.com/ndk/downloads)
 * Android phone with Snapdragon8 Gen3 (SM8650) or Gen2 (SM8550). Gen 1 and lower SoC might be supported but not fully validated.
 * Desired Llama model weights in .PTH format. You can download them on HuggingFace ([Example](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)).