diff --git a/tensorflow/lite/micro/kernels/cmsis_nn/conv.cc b/tensorflow/lite/micro/kernels/cmsis_nn/conv.cc
index 6691b59..4c35970 100644
--- a/tensorflow/lite/micro/kernels/cmsis_nn/conv.cc
+++ b/tensorflow/lite/micro/kernels/cmsis_nn/conv.cc
@@ -21,7 +21,6 @@
 #include "tensorflow/lite/kernels/internal/common.h"
 #include "tensorflow/lite/kernels/internal/quantization_util.h"
 #include "tensorflow/lite/kernels/internal/reference/conv.h"
-#include "tensorflow/lite/kernels/internal/reference/integer_ops/conv.h"
 #include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
 #include "tensorflow/lite/kernels/kernel_util.h"
 #include "tensorflow/lite/kernels/padding.h"
@@ -214,9 +213,26 @@
     const cmsis_nn_dims* filter_dims, const int8_t* filter,
     const cmsis_nn_dims* bias_dims, const int64_t* bias,
     const cmsis_nn_dims* output_dims, int16_t* output, TfLiteType weightsT) {
+  const cmsis_nn_bias_data bias_data = {bias, false};
+
   return arm_convolve_wrapper_s16(ctx, conv_params, quant_params, input_dims,
-                                  input, filter_dims, filter, bias_dims, bias,
-                                  output_dims, output);
+                                  input, filter_dims, filter, bias_dims,
+                                  &bias_data, output_dims, output);
+}
+
+template <>
+arm_cmsis_nn_status convolve_wrapper(
+    const cmsis_nn_context* ctx, const cmsis_nn_conv_params* conv_params,
+    const cmsis_nn_per_channel_quant_params* quant_params,
+    const cmsis_nn_dims* input_dims, const int16_t* input,
+    const cmsis_nn_dims* filter_dims, const int8_t* filter,
+    const cmsis_nn_dims* bias_dims, const int32_t* bias,
+    const cmsis_nn_dims* output_dims, int16_t* output, TfLiteType weightsT) {
+  const cmsis_nn_bias_data bias_data = {bias, true};
+
+  return arm_convolve_wrapper_s16(ctx, conv_params, quant_params, input_dims,
+                                  input, filter_dims, filter, bias_dims,
+                                  &bias_data, output_dims, output);
 }
 
 template <typename ActType, typename BiasType, TfLiteType type>
@@ -362,25 +378,17 @@
   TFLITE_DCHECK(node->user_data != nullptr);
   const OpData& data = *(static_cast<const OpData*>(node->user_data));
 
-  if (bias == nullptr || bias->type == kTfLiteInt64) {
+  if (bias == nullptr || bias->type == kTfLiteInt32) {
+    return EvalQuantizedPerChannel<int16_t, int32_t, kTfLiteInt16>(
+        context, node, params, data, input, filter, bias, output);
+  } else if (bias->type == kTfLiteInt64) {
     return EvalQuantizedPerChannel<int16_t, int64_t, kTfLiteInt16>(
         context, node, params, data, input, filter, bias, output);
   } else {
-    reference_integer_ops::ConvPerChannel(
-        ConvParamsQuantized(params, data.reference_op_data),
-        data.reference_op_data.per_channel_output_multiplier,
-        data.reference_op_data.per_channel_output_shift,
-        tflite::micro::GetTensorShape(input),
-        tflite::micro::GetTensorData<int16_t>(input),
-        tflite::micro::GetTensorShape(filter),
-        tflite::micro::GetTensorData<int8_t>(filter),
-        tflite::micro::GetTensorShape(bias),
-        tflite::micro::GetOptionalTensorData<std::int32_t>(bias),
-        tflite::micro::GetTensorShape(output),
-        tflite::micro::GetTensorData<int16_t>(output));
+    MicroPrintf("Bias type %s (%d) not supported.",
+                TfLiteTypeGetName(bias->type), bias->type);
+    return kTfLiteError;
   }
-
-  return kTfLiteOk;
 }
 
 TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
@@ -443,22 +451,12 @@
       break;
     }
     case kTfLiteInt16: {
-      if (bias == nullptr || bias->type == kTfLiteInt64) {
+      if (bias == nullptr || bias->type == kTfLiteInt32) {
+        return EvalQuantizedPerChannel<int16_t, int32_t, kTfLiteInt16>(
+            context, node, params, data, input, filter, bias, output);
+      } else if (bias->type == kTfLiteInt64) {
         return EvalQuantizedPerChannel<int16_t, int64_t, kTfLiteInt16>(
             context, node, params, data, input, filter, bias, output);
-      } else if (bias->type == kTfLiteInt32) {
-        reference_integer_ops::ConvPerChannel(
-            ConvParamsQuantized(params, data.reference_op_data),
-            data.reference_op_data.per_channel_output_multiplier,
-            data.reference_op_data.per_channel_output_shift,
-            tflite::micro::GetTensorShape(input),
-            tflite::micro::GetTensorData<int16_t>(input),
-            tflite::micro::GetTensorShape(filter),
-            tflite::micro::GetTensorData<int8_t>(filter),
-            tflite::micro::GetTensorShape(bias),
-            tflite::micro::GetOptionalTensorData<std::int32_t>(bias),
-            tflite::micro::GetTensorShape(output),
-            tflite::micro::GetTensorData<int16_t>(output));
       } else {
         MicroPrintf("Bias type %s (%d) not supported.",
                     TfLiteTypeGetName(bias->type), bias->type);
diff --git a/tensorflow/lite/micro/tools/make/ext_libs/cmsis_nn_download.sh b/tensorflow/lite/micro/tools/make/ext_libs/cmsis_nn_download.sh
index 482766c..195c0ca 100755
--- a/tensorflow/lite/micro/tools/make/ext_libs/cmsis_nn_download.sh
+++ b/tensorflow/lite/micro/tools/make/ext_libs/cmsis_nn_download.sh
@@ -47,9 +47,9 @@
   echo >&2 "${DOWNLOADED_CMSIS_NN_PATH} already exists, skipping the download."
 else
 
-  ZIP_PREFIX_NN="8492d82a1a81651977c5f5128492b4a0f0cf6715"
+  ZIP_PREFIX_NN="15dbe7cda7130766777f18a69388238bc6540cef"
   CMSIS_NN_URL="http://github.com/ARM-software/CMSIS-NN/archive/${ZIP_PREFIX_NN}.zip"
-  CMSIS_NN_MD5="2cb03e4f044b78af6751009cd53247a8"
+  CMSIS_NN_MD5="6121fa707d4dac17acb4e222453a38a6"
 
   # wget is much faster than git clone of the entire repo. So we wget a specific
   # version and can then apply a patch, as needed.