diff --git a/run_llm_inference.sh b/run_llm_inference.sh
new file mode 100644
index 0000000000..62f1a440de
--- /dev/null
+++ b/run_llm_inference.sh
@@ -0,0 +1,38 @@
+#!/bin/bash
+
+# This is a simple script to run LLM inference on Android via the MediaPipe
+# LLM inference engine.
+
+MODEL_FILENAME="gemma2-2b-it-cpu-int8.task"
+ADB_WORK_DIR="/data/local/tmp"
+INPUT_PROMPT="What is the most famous building in Paris?"
+
+if [ ! -f "${MODEL_FILENAME}" ]; then
+  echo "Error: ${MODEL_FILENAME} not found."
+  echo "Please download it from https://www.kaggle.com/models/google/gemma-2/tfLite/gemma2-2b-it-cpu-int8"
+  exit 1
+fi
+
+adb push "${MODEL_FILENAME}" "${ADB_WORK_DIR}/${MODEL_FILENAME}"
+
+# Build the MediaPipe Docker base image.
+docker build . --tag=mediapipe
+
+# Build the LLM inference engine binary and copy to the conencted Android device.
+CONTAINER_NAME=mediapipe_$(cat /dev/urandom | tr -dc 'a-zA-Z0-9' | fold -w 10 | head -n 1)
+docker run --name "$CONTAINER_NAME" mediapipe:latest  sh -c "
+    chmod +x  setup_android_sdk_and_ndk.sh && \
+    ./setup_android_sdk_and_ndk.sh ~/Android/Sdk ~/Android/Ndk r26d \
+        --accept-licenses &&
+    bazel build --config android_arm64 --client_env=CC=clang-16 -c opt \
+        --copt=-DABSL_FLAGS_STRIP_NAMES=0 \
+        --host_crosstool_top=@bazel_tools//tools/cpp:toolchain \
+        //mediapipe/tasks/cc/genai/inference/c:llm_inference_engine_cpu_main
+"
+docker cp "$CONTAINER_NAME":/mediapipe/bazel-bin/mediapipe/tasks/cc/genai/inference/c/llm_inference_engine_cpu_main llm_inference_engine_cpu_main
+adb push llm_inference_engine_cpu_main "${ADB_WORK_DIR}"/llm_inference_engine_cpu_main
+
+# Run the inference.
+adb shell "taskset f0 ${ADB_WORK_DIR}/llm_inference_engine_cpu_main \
+              --model_path='${ADB_WORK_DIR}/${MODEL_FILENAME}' \
+              --prompt='${INPUT_PROMPT}'"