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+Minibench: ExecuTorch Android Benchmark App
+===
+
+Minibench is a benchmarking app for testing the performance of the ExecuTorch runtime on Android devices.
+
+It supports both generic (vision, audio, etc) models and LLM.
+
+- For generic model, it reports metrics such as model load time, and average inference time.
+- For LLM, it reports metrics such as model load time, and tokens per second.
+- We are working on providing more metrics in the future.
+
+Minibench is usedful for giving reference performance data when developers integrate ExecuTorch with their own Android app.
+
+## Build
+You will need executorch AAR for Java and JNI dependencies.
+```
+export ANDROID_NDK=<path_to_android_ndk>
+sh build/build_android_llm_demo.sh
+```
+and copy the AAR to `app/libs`.
+```
+mkdir -p app/libs
+cp $BUILD_AAR_DIR/executorch.aar app/libs
+```
+
+You can also refer to [this script](https://github.com/pytorch/executorch/blob/62024d8/.github/workflows/android-perf.yml#L226-L235) to see how it is built.
+
+Then you can build and install the app on Android Studio, or simply run
+```
+./gradlew installDebug
+```
+
+## Usage
+This apk does not come with a launcher icon. Instead, trigger it from command line
+
+### Push model to a directory
+```
+adb shell mkdir /data/local/tmp/minibench
+adb push my_model.pte /data/local/tmp/minibench
+# optionally, push tokenizer for LLM
+adb push tokenizer.bin /data/local/tmp/minibench
+```
+
+### Generic model
+```
+adb shell am start -W -S -n org.pytorch.minibench/org.pytorch.minibench.LlmBenchmarkActivity \
+ --es model_dir /data/local/tmp/minibench
+```
+
+### LLM
+```
+adb shell am start -W -S -n org.pytorch.minibench/org.pytorch.minibench.LlmBenchmarkActivity \
+ --es model_dir /data/local/tmp/minibench --es tokenizer_path /data/local/tmp/minibench/tokenizer.bin
+```
+
+### Fetch results
+```
+adb shell run-as org.pytorch.minibench cat files/benchmark_results.json
+```
+If the ExecuTorch runner is initialized and loads your model, but there is a load error or run error, you will see error code from that JSON.