diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
index b35b36475..278689915 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
@@ -105,7 +105,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
   typedef typename XprType::CoeffReturnType CoeffReturnType;
   typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
   static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
-  bool nByOne = false, oneByN = false;
+  bool isCopy= false, nByOne = false, oneByN = false;
 
   enum {
     IsAligned = true,
@@ -122,10 +122,13 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
     // tensor with N >= 1 of 1 element first and then broadcast.
     EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
     const InputDimensions& input_dims = m_impl.dimensions();
-    const Broadcast& broadcast = op.broadcast();
+    isCopy = true;
     for (int i = 0; i < NumDims; ++i) {
       eigen_assert(input_dims[i] > 0);
-      m_dimensions[i] = input_dims[i] * broadcast[i];
+      m_dimensions[i] = input_dims[i] * m_broadcast[i];
+      if (m_broadcast[i] != 1) {
+        isCopy = false;
+      }
     }
 
     if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
@@ -147,7 +150,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
     if (input_dims[0] == 1) {
       oneByN = true;
       for (int i = 1; i < NumDims; ++i) {
-        if (broadcast[i] != 1) {
+        if (m_broadcast[i] != 1) {
           oneByN = false;
           break;
         }
@@ -155,7 +158,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
     } else if (input_dims[NumDims-1] == 1) {
       nByOne = true;
       for (int i = 0; i < NumDims-1; ++i) {
-        if (broadcast[i] != 1) {
+        if (m_broadcast[i] != 1) {
           nByOne = false;
           break;
         }
@@ -169,7 +172,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
         nByOne = true;
         oneByN = true;
         for (int i = 1; i < NumDims-1; ++i) {
-          if (broadcast[i] != 1) {
+          if (m_broadcast[i] != 1) {
             nByOne = false;
             oneByN = false;
             break;
@@ -197,9 +200,17 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
     }
 
     if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
-      return coeffColMajor(index);
+      if (isCopy) {
+        return m_impl.coeff(index);
+      } else {
+        return coeffColMajor(index);
+      }
     } else {
-      return coeffRowMajor(index);
+      if (isCopy) {
+        return m_impl.coeff(index);
+      } else {
+        return coeffRowMajor(index);
+      }
     }
   }
 
@@ -272,7 +283,9 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
     }
 
     if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
-      if (oneByN && !nByOne) {
+      if (isCopy) {
+        return m_impl.template packet<LoadMode>(index);
+      } else if (oneByN && !nByOne) {
         return packetNByOne<LoadMode>(index);
       } else if (!oneByN && nByOne) {
         return packetOneByN<LoadMode>(index);
@@ -282,7 +295,9 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
         return packetColMajor<LoadMode>(index);
       }
     } else {
-      if (oneByN && !nByOne) {
+      if (isCopy) {
+        return m_impl.template packet<LoadMode>(index);
+      } else if (oneByN && !nByOne) {
         return packetOneByN<LoadMode>(index);
       } else if (!oneByN && nByOne) {
         return packetNByOne<LoadMode>(index);
@@ -516,7 +531,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
   costPerCoeff(bool vectorized) const {
     double compute_cost = TensorOpCost::AddCost<Index>();
-    if (NumDims > 0) {
+    if (!isCopy && NumDims > 0) {
       for (int i = NumDims - 1; i > 0; --i) {
         compute_cost += TensorOpCost::DivCost<Index>();
         if (internal::index_statically_eq<Broadcast>(i, 1)) {