diff --git a/extension/android/executorch_android/src/main/java/org/pytorch/executorch/extension/llm/LlmModule.java b/extension/android/executorch_android/src/main/java/org/pytorch/executorch/extension/llm/LlmModule.java
index 3c586bf7577..93c432e78f6 100644
--- a/extension/android/executorch_android/src/main/java/org/pytorch/executorch/extension/llm/LlmModule.java
+++ b/extension/android/executorch_android/src/main/java/org/pytorch/executorch/extension/llm/LlmModule.java
@@ -186,7 +186,7 @@ public int generate(
   }
 
   /**
-   * Prefill an LLaVA Module with the given images input.
+   * Prefill a multimodal Module with the given images input.
    *
    * @param image Input image as a byte array
    * @param width Input image width
@@ -196,7 +196,7 @@ public int generate(
    *     exposed to user.
    * @throws RuntimeException if the prefill failed
    */
-  @Deprecated
+  @Experimental
   public long prefillImages(int[] image, int width, int height, int channels) {
     int nativeResult = appendImagesInput(image, width, height, channels);
     if (nativeResult != 0) {
@@ -208,7 +208,7 @@ public long prefillImages(int[] image, int width, int height, int channels) {
   private native int appendImagesInput(int[] image, int width, int height, int channels);
 
   /**
-   * Prefill an LLaVA Module with the given images input.
+   * Prefill a multimodal Module with the given images input.
    *
    * @param image Input normalized image as a float array
    * @param width Input image width
@@ -218,7 +218,7 @@ public long prefillImages(int[] image, int width, int height, int channels) {
    *     exposed to user.
    * @throws RuntimeException if the prefill failed
    */
-  @Deprecated
+  @Experimental
   public long prefillImages(float[] image, int width, int height, int channels) {
     int nativeResult = appendNormalizedImagesInput(image, width, height, channels);
     if (nativeResult != 0) {
@@ -231,14 +231,59 @@ private native int appendNormalizedImagesInput(
       float[] image, int width, int height, int channels);
 
   /**
-   * Prefill an LLaVA Module with the given text input.
+   * Prefill a multimodal Module with the given audio input.
    *
-   * @param prompt The text prompt to LLaVA.
+   * @param audio Input preprocessed audio as a byte array
+   * @param batch_size Input batch size
+   * @param n_bins Input number of bins
+   * @param n_frames Input number of frames
    * @return 0, as the updated starting position in KV cache of the input in the LLM is no longer
    *     exposed to user.
    * @throws RuntimeException if the prefill failed
    */
-  @Deprecated
+  @Experimental
+  public long prefillAudio(byte[] audio, int batch_size, int n_bins, int n_frames) {
+    int nativeResult = appendAudioInput(audio, batch_size, n_bins, n_frames);
+    if (nativeResult != 0) {
+      throw new RuntimeException("Prefill failed with error code: " + nativeResult);
+    }
+    return 0;
+  }
+
+  private native int appendAudioInput(byte[] audio, int batch_size, int n_bins, int n_frames);
+
+  /**
+   * Prefill a multimodal Module with the given raw audio input.
+   *
+   * @param audio Input raw audio as a byte array
+   * @param batch_size Input batch size
+   * @param n_channels Input number of channels
+   * @param n_samples Input number of samples
+   * @return 0, as the updated starting position in KV cache of the input in the LLM is no longer
+   *     exposed to user.
+   * @throws RuntimeException if the prefill failed
+   */
+  @Experimental
+  public long prefillRawAudio(byte[] audio, int batch_size, int n_channels, int n_samples) {
+    int nativeResult = appendRawAudioInput(audio, batch_size, n_channels, n_samples);
+    if (nativeResult != 0) {
+      throw new RuntimeException("Prefill failed with error code: " + nativeResult);
+    }
+    return 0;
+  }
+
+  private native int appendRawAudioInput(
+      byte[] audio, int batch_size, int n_channels, int n_samples);
+
+  /**
+   * Prefill a multimodal Module with the given text input.
+   *
+   * @param prompt The text prompt to prefill.
+   * @return 0, as the updated starting position in KV cache of the input in the LLM is no longer
+   *     exposed to user.
+   * @throws RuntimeException if the prefill failed
+   */
+  @Experimental
   public long prefillPrompt(String prompt) {
     int nativeResult = appendTextInput(prompt);
     if (nativeResult != 0) {
diff --git a/extension/android/jni/jni_layer_llama.cpp b/extension/android/jni/jni_layer_llama.cpp
index d12783d4cf0..ae1d0a83201 100644
--- a/extension/android/jni/jni_layer_llama.cpp
+++ b/extension/android/jni/jni_layer_llama.cpp
@@ -316,6 +316,53 @@ class ExecuTorchLlmJni : public facebook::jni::HybridClass<ExecuTorchLlmJni> {
     return 0;
   }
 
+  // Returns status_code
+  jint append_audio_input(
+      facebook::jni::alias_ref<jbyteArray> data,
+      jint batch_size,
+      jint n_bins,
+      jint n_frames) {
+    if (data == nullptr) {
+      return static_cast<jint>(Error::EndOfMethod);
+    }
+    auto data_size = data->size();
+    if (data_size != 0) {
+      std::vector<jbyte> data_jbyte(data_size);
+      std::vector<uint8_t> data_u8(data_size);
+      data->getRegion(0, data_size, data_jbyte.data());
+      for (int i = 0; i < data_size; i++) {
+        data_u8[i] = data_jbyte[i];
+      }
+      llm::Audio audio{std::move(data_u8), batch_size, n_bins, n_frames};
+      prefill_inputs_.emplace_back(llm::MultimodalInput{std::move(audio)});
+    }
+    return 0;
+  }
+
+  // Returns status_code
+  jint append_raw_audio_input(
+      facebook::jni::alias_ref<jbyteArray> data,
+      jint batch_size,
+      jint n_channels,
+      jint n_samples) {
+    if (data == nullptr) {
+      return static_cast<jint>(Error::EndOfMethod);
+    }
+    auto data_size = data->size();
+    if (data_size != 0) {
+      std::vector<jbyte> data_jbyte(data_size);
+      std::vector<uint8_t> data_u8(data_size);
+      data->getRegion(0, data_size, data_jbyte.data());
+      for (int i = 0; i < data_size; i++) {
+        data_u8[i] = data_jbyte[i];
+      }
+      llm::RawAudio audio{
+          std::move(data_u8), batch_size, n_channels, n_samples};
+      prefill_inputs_.emplace_back(llm::MultimodalInput{std::move(audio)});
+    }
+    return 0;
+  }
+
   void stop() {
     if (model_type_category_ == MODEL_TYPE_CATEGORY_MULTIMODAL) {
       multi_modal_runner_->stop();
@@ -353,6 +400,10 @@ class ExecuTorchLlmJni : public facebook::jni::HybridClass<ExecuTorchLlmJni> {
         makeNativeMethod(
             "appendNormalizedImagesInput",
             ExecuTorchLlmJni::append_normalized_images_input),
+        makeNativeMethod(
+            "appendAudioInput", ExecuTorchLlmJni::append_audio_input),
+        makeNativeMethod(
+            "appendRawAudioInput", ExecuTorchLlmJni::append_raw_audio_input),
         makeNativeMethod(
             "appendTextInput", ExecuTorchLlmJni::append_text_input),
         makeNativeMethod("resetContext", ExecuTorchLlmJni::reset_context),