diff --git a/.ci/scripts/export_model_artifact.sh b/.ci/scripts/export_model_artifact.sh
index 3c173b0ea2a..b628af7b694 100755
--- a/.ci/scripts/export_model_artifact.sh
+++ b/.ci/scripts/export_model_artifact.sh
@@ -51,9 +51,10 @@ fi
 set -eux
 
 DEVICE="$1"
-HF_MODEL="$2"
-QUANT_NAME="${3:-non-quantized}"
-OUTPUT_DIR="${4:-.}"
+DTYPE="$2"
+HF_MODEL="$3"
+QUANT_NAME="${4:-non-quantized}"
+OUTPUT_DIR="${5:-.}"
 
 case "$DEVICE" in
   cuda)
@@ -67,6 +68,18 @@ case "$DEVICE" in
     ;;
 esac
 
+case "$DTYPE" in
+  float16)
+    ;;
+  bfloat16)
+    ;;
+  *)
+    echo "Error: Unsupported dtype '$DTYPE'"
+    echo "Supported dtypes: float16, bfloat16"
+    exit 1
+    ;;
+esac
+
 # Determine model configuration based on HF model ID
 case "$HF_MODEL" in
   mistralai/Voxtral-Mini-3B-2507)
@@ -155,7 +168,7 @@ optimum-cli export executorch \
     --model "$HF_MODEL" \
     --task "$TASK" \
     --recipe "$DEVICE" \
-    --dtype bfloat16 \
+    --dtype "$DTYPE" \
     ${DEVICE_ARG} \
     ${MAX_SEQ_LEN_ARG} \
     ${EXTRA_ARGS} \
diff --git a/.github/workflows/cuda.yml b/.github/workflows/cuda.yml
index c66d3621ea1..cd513de18a5 100644
--- a/.github/workflows/cuda.yml
+++ b/.github/workflows/cuda.yml
@@ -142,7 +142,7 @@ jobs:
         pip install git+https://github.com/huggingface/optimum-executorch.git@${OPTIMUM_ET_VERSION}
         echo "::endgroup::"
 
-        source .ci/scripts/export_model_artifact.sh cuda "${{ matrix.model.repo }}/${{ matrix.model.name }}" "${{ matrix.quant }}" "${RUNNER_ARTIFACT_DIR}"
+        source .ci/scripts/export_model_artifact.sh cuda bfloat16 "${{ matrix.model.repo }}/${{ matrix.model.name }}" "${{ matrix.quant }}" "${RUNNER_ARTIFACT_DIR}"
 
   test-model-cuda-e2e:
     name: test-model-cuda-e2e
diff --git a/.github/workflows/metal.yml b/.github/workflows/metal.yml
index 92351883e8f..01bb446432d 100644
--- a/.github/workflows/metal.yml
+++ b/.github/workflows/metal.yml
@@ -44,6 +44,9 @@ jobs:
             name: "whisper-small"
           - repo: "openai"
             name: "whisper-large-v3-turbo"
+        dtype:
+          - "float16"
+          - "bfloat16"
         quant:
           - "non-quantized"
     with:
@@ -53,7 +56,7 @@ jobs:
       ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
       timeout: 90
       secrets-env: EXECUTORCH_HF_TOKEN
-      upload-artifact: ${{ matrix.model.repo }}-${{ matrix.model.name }}-metal-${{ matrix.quant }}
+      upload-artifact: ${{ matrix.model.repo }}-${{ matrix.model.name }}-metal-${{ matrix.dtype }}-${{ matrix.quant }}
       script: |
         set -eux
 
@@ -76,7 +79,7 @@ jobs:
         ${CONDA_RUN} pip list
         echo "::endgroup::"
 
-        ${CONDA_RUN} bash .ci/scripts/export_model_artifact.sh metal "${{ matrix.model.repo }}/${{ matrix.model.name }}" "${{ matrix.quant }}" "${RUNNER_ARTIFACT_DIR}"
+        ${CONDA_RUN} bash .ci/scripts/export_model_artifact.sh metal "${{ matrix.dtype }}" "${{ matrix.model.repo }}/${{ matrix.model.name }}" "${{ matrix.quant }}" "${RUNNER_ARTIFACT_DIR}"
 
   test-model-metal-e2e:
     name: test-model-metal-e2e
@@ -92,6 +95,9 @@ jobs:
             name: "whisper-small"
           - repo: "openai"
             name: "whisper-large-v3-turbo"
+        dtype:
+          - "float16"
+          - "bfloat16"
         quant:
           - "non-quantized"
     with:
@@ -100,7 +106,7 @@ jobs:
       submodules: 'recursive'
       ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
       timeout: 90
-      download-artifact: ${{ matrix.model.repo }}-${{ matrix.model.name }}-metal-${{ matrix.quant }}
+      download-artifact: ${{ matrix.model.repo }}-${{ matrix.model.name }}-metal-${{ matrix.dtype }}-${{ matrix.quant }}
       script: |
         set -eux
 
diff --git a/backends/aoti/common_shims.cpp b/backends/aoti/common_shims.cpp
index abfde86db6d..0661d327f20 100644
--- a/backends/aoti/common_shims.cpp
+++ b/backends/aoti/common_shims.cpp
@@ -170,6 +170,10 @@ int32_t aoti_torch_dtype_float32() {
   return 6; // PyTorch's float32 dtype code
 }
 
+int32_t aoti_torch_dtype_float16() {
+  return 5; // PyTorch's float16 dtype code
+}
+
 int32_t aoti_torch_dtype_bfloat16() {
   return 15; // PyTorch's bfloat16 dtype code
 }
diff --git a/backends/aoti/common_shims.h b/backends/aoti/common_shims.h
index 675a9864e74..95825eadedd 100644
--- a/backends/aoti/common_shims.h
+++ b/backends/aoti/common_shims.h
@@ -63,6 +63,7 @@ aoti_torch_get_dim(Tensor* tensor, int64_t* ret_dim);
 AOTI_SHIM_EXPORT int32_t aoti_torch_device_type_cpu();
 AOTI_SHIM_EXPORT int32_t aoti_torch_layout_strided();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_float32();
+AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_float16();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_bfloat16();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_int8();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_int16();
diff --git a/backends/aoti/utils.h b/backends/aoti/utils.h
index 8f64bdbe7da..ddef8cfd94a 100644
--- a/backends/aoti/utils.h
+++ b/backends/aoti/utils.h
@@ -43,6 +43,8 @@ inline executorch::aten::ScalarType dtype_to_scalar_type(int32_t dtype) {
       return executorch::aten::ScalarType::Int;
     case 4: // PyTorch's int64 dtype code
       return executorch::aten::ScalarType::Long;
+    case 5: // PyTorch's float16 dtype code
+      return executorch::aten::ScalarType::Half;
     case 6: // PyTorch's float32 dtype code
       return executorch::aten::ScalarType::Float;
     case 11: // PyTorch's bool dtype code
diff --git a/backends/apple/metal/runtime/shims/et_metal_ops.mm b/backends/apple/metal/runtime/shims/et_metal_ops.mm
index b150c68fe6d..a323cc7f225 100644
--- a/backends/apple/metal/runtime/shims/et_metal_ops.mm
+++ b/backends/apple/metal/runtime/shims/et_metal_ops.mm
@@ -224,12 +224,15 @@ AOTITorchError aoti_torch_mps_mm_out(
       MPSDataType mps_dtype;
       size_t element_size;
 
-      ET_LOG(Debug, "aoti_torch_mps_mm_out: self_tensor scalar_type=%d, SupportedDTypes::FLOAT32=%d, SupportedDTypes::BFLOAT16=%d",
-             dtype, static_cast<int32_t>(SupportedDTypes::FLOAT32), static_cast<int32_t>(SupportedDTypes::BFLOAT16));
+      ET_LOG(Debug, "aoti_torch_mps_mm_out: self_tensor scalar_type=%d, SupportedDTypes::FLOAT32=%d, SupportedDTypes::FLOAT16=%d, SupportedDTypes::BFLOAT16=%d",
+             dtype, static_cast<int32_t>(SupportedDTypes::FLOAT32), static_cast<int32_t>(SupportedDTypes::FLOAT16), static_cast<int32_t>(SupportedDTypes::BFLOAT16));
 
       if (dtype == static_cast<int32_t>(SupportedDTypes::FLOAT32)) {
         mps_dtype = MPSDataTypeFloat32;
         element_size = sizeof(float);
+      } else if (dtype == static_cast<int32_t>(SupportedDTypes::FLOAT16)) {
+        mps_dtype = MPSDataTypeFloat16;
+        element_size = sizeof(uint16_t);  // half is 16 bits
       } else if (dtype == static_cast<int32_t>(SupportedDTypes::BFLOAT16)) {
         mps_dtype = MPSDataTypeBFloat16;
         element_size = sizeof(uint16_t);  // bfloat16 is 16 bits
@@ -592,6 +595,9 @@ AOTITorchError aoti_torch_mps_convolution(
       if (dtype == static_cast<int32_t>(SupportedDTypes::FLOAT32)) {
         mps_dtype = MPSDataTypeFloat32;
         element_size = sizeof(float);
+      } else if (dtype == static_cast<int32_t>(SupportedDTypes::FLOAT16)) {
+        mps_dtype = MPSDataTypeFloat16;
+        element_size = sizeof(uint16_t);  // half is 16 bits
       } else if (dtype == static_cast<int32_t>(SupportedDTypes::BFLOAT16)) {
         mps_dtype = MPSDataTypeBFloat16;
         element_size = sizeof(uint16_t);  // bfloat16 is 16 bits
@@ -1084,6 +1090,9 @@ AOTITorchError aoti_torch_mps__scaled_dot_product_attention_math_for_mps(
         if (dtype == static_cast<int32_t>(SupportedDTypes::FLOAT32)) {
           mps_dtype = MPSDataTypeFloat32;
           element_size = sizeof(float);
+        } else if (dtype == static_cast<int32_t>(SupportedDTypes::FLOAT16)) {
+          mps_dtype = MPSDataTypeFloat16;
+          element_size = sizeof(uint16_t);  // half is 16 bits
         } else if (dtype == static_cast<int32_t>(SupportedDTypes::BFLOAT16)) {
           mps_dtype = MPSDataTypeBFloat16;
           element_size = sizeof(uint16_t);  // bfloat16 is 16 bits
diff --git a/backends/apple/metal/runtime/shims/utils.cpp b/backends/apple/metal/runtime/shims/utils.cpp
index 061360a4e28..b24aa49d7b8 100644
--- a/backends/apple/metal/runtime/shims/utils.cpp
+++ b/backends/apple/metal/runtime/shims/utils.cpp
@@ -21,6 +21,7 @@ bool is_dtype_supported_in_et_metal(int32_t dtype) {
   switch (dtype) {
     case static_cast<int32_t>(SupportedDTypes::INT64):
     case static_cast<int32_t>(SupportedDTypes::FLOAT32):
+    case static_cast<int32_t>(SupportedDTypes::FLOAT16):
     case static_cast<int32_t>(SupportedDTypes::BFLOAT16):
       return true;
     default:
@@ -40,6 +41,7 @@ AOTITorchError validate_dtype(int32_t dtype) {
       dtype,
       static_cast<int32_t>(SupportedDTypes::INT64),
       static_cast<int32_t>(SupportedDTypes::FLOAT32),
+      static_cast<int32_t>(SupportedDTypes::FLOAT16),
       static_cast<int32_t>(SupportedDTypes::BFLOAT16));
   return Error::InvalidArgument;
 }
diff --git a/backends/apple/metal/runtime/shims/utils.h b/backends/apple/metal/runtime/shims/utils.h
index 974832fa365..9c1b2449aaa 100644
--- a/backends/apple/metal/runtime/shims/utils.h
+++ b/backends/apple/metal/runtime/shims/utils.h
@@ -24,7 +24,7 @@ enum class SupportedDTypes : int32_t {
   // INT16 = 2,    // PyTorch's int16 dtype code
   // INT32 = 3,    // PyTorch's int32 dtype code
   INT64 = 4, // PyTorch's int64 dtype code
-  // FLOAT16 = 5,  // PyTorch's float16 dtype code
+  FLOAT16 = 5, // PyTorch's float16 dtype code
   FLOAT32 = 6, // PyTorch's float32 dtype code
   // FLOAT64 = 7,  // PyTorch's float64 dtype code
   // BOOL = 11,    // PyTorch's bool dtype code
diff --git a/extension/asr/runner/runner.cpp b/extension/asr/runner/runner.cpp
index 4f2523989c1..6848f272344 100644
--- a/extension/asr/runner/runner.cpp
+++ b/extension/asr/runner/runner.cpp
@@ -192,7 +192,24 @@ Result<std::vector<int64_t>> AsrRunner::transcribe(
           Info,
           "Conversion complete, first value = %f",
           static_cast<float>(
-              preprocessed_features->mutable_data_ptr<float>()[0]));
+              preprocessed_features
+                  ->mutable_data_ptr<::executorch::aten::BFloat16>()[0]));
+    } else if (expected_dtype == ::executorch::aten::ScalarType::Half) {
+      ET_LOG(
+          Info,
+          "Converting audio features from %s to Float16 (Half). Before converting, first value = %f",
+          ::executorch::runtime::toString(preprocessed_features->scalar_type()),
+          preprocessed_features->mutable_data_ptr<float>()[0]);
+      auto convert_result = ::executorch::extension::llm::convert_to_float16(
+          preprocessed_features);
+      ET_CHECK_OK_OR_RETURN_ERROR(convert_result.error());
+      preprocessed_features = convert_result.get();
+      ET_LOG(
+          Info,
+          "Conversion complete, first value = %f",
+          static_cast<float>(
+              preprocessed_features
+                  ->mutable_data_ptr<::executorch::aten::Half>()[0]));
     }
   }
 
diff --git a/extension/llm/runner/util.h b/extension/llm/runner/util.h
index e87d625f140..66de249b90f 100644
--- a/extension/llm/runner/util.h
+++ b/extension/llm/runner/util.h
@@ -174,6 +174,30 @@ convert_to_bfloat16(const ::executorch::extension::TensorPtr& src_tensor) {
   return bf16_tensor;
 }
 
+/**
+ * Helper function to convert a float tensor to float16 (Half).
+ * Creates a new tensor with Half dtype and copies/converts the data.
+ */
+inline ::executorch::runtime::Result<::executorch::extension::TensorPtr>
+convert_to_float16(const ::executorch::extension::TensorPtr& src_tensor) {
+  ET_CHECK_OR_RETURN_ERROR(
+      src_tensor->scalar_type() == ::executorch::aten::ScalarType::Float,
+      InvalidArgument,
+      "Float16 conversion only supported from Float source data");
+
+  const auto num_elements = static_cast<size_t>(src_tensor->numel());
+  const float* float_data = src_tensor->const_data_ptr<float>();
+
+  auto f16_tensor = ::executorch::extension::empty_like(
+      src_tensor, ::executorch::aten::ScalarType::Half);
+  auto* f16_data = f16_tensor->mutable_data_ptr<::executorch::aten::Half>();
+  for (size_t i = 0; i < num_elements; ++i) {
+    f16_data[i] = ::executorch::aten::Half(float_data[i]);
+  }
+
+  return f16_tensor;
+}
+
 } // namespace llm
 } // namespace extension
 } // namespace executorch