diff --git a/libnd4j/include/ops/declarable/helpers/cuda/addBias.cu b/libnd4j/include/ops/declarable/helpers/cuda/addBias.cu
index 3fc5d42c9..dad5a5b06 100644
--- a/libnd4j/include/ops/declarable/helpers/cuda/addBias.cu
+++ b/libnd4j/include/ops/declarable/helpers/cuda/addBias.cu
@@ -91,19 +91,55 @@ static void addBiasCudaLauncher(const int blocksPerGrid, const int threadsPerBlo
     addBiasCuda<X,Y><<<blocksPerGrid, threadsPerBlock, sharedMem, *stream>>>(vx, xShapeInfo, vy, yShapeInfo, vz, zShapeInfo, isNCHW);
 }
 
+template<typename X, typename Y>
+__global__ static void addBias2DCuda( const void* vx,
+                                        const void* vy,
+                                        void* vz,
+                                        uint32_t blocks, uint32_t length) {
+
+    auto y = reinterpret_cast<const Y*>(vy);
+
+    for (uint32_t b = blockIdx.x; b < blocks; b += gridDim.x) {
+        auto x = reinterpret_cast<const X*>(vx) + length * b;
+        auto z = reinterpret_cast<X*>(vz) + length * b;
+
+        for (uint32_t e = threadIdx.x; e < length; e += blockDim.x) {
+            z[e] = x[e] + y[e];
+        }
+    }
+}
+
+template<typename X, typename Y>
+static void addBias2DCudaLauncher(const cudaStream_t *stream, const void* vx,
+                                  const void* vy,
+                                  void* vz,
+                                  uint32_t blocks, uint32_t length) {
+
+    addBias2DCuda<X,Y><<<256, 1024, 128, *stream>>>(vx, vy, vz, blocks, length);
+}
+
 //////////////////////////////////////////////////////////////////////////
 void addBias(sd::graph::Context& block, const NDArray& input, const NDArray& bias, NDArray& output, const bool isNCHW) {
 
     PointersManager manager(block.launchContext(), "addBias");
-
-    const int threadsPerBlock = MAX_NUM_THREADS/2;
-    const int blocksPerGrid = (input.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
-    const int sharedMem = input.rankOf() * sizeof(Nd4jLong) * threadsPerBlock  + 128;
-
     NDArray::prepareSpecialUse({&output}, {&input, &bias});
-    BUILD_DOUBLE_SELECTOR(input.dataType(), bias.dataType(), addBiasCudaLauncher, (blocksPerGrid, threadsPerBlock, sharedMem, block.launchContext()->getCudaStream(), input.getSpecialBuffer(), input.getSpecialShapeInfo(), bias.getSpecialBuffer(), bias.getSpecialShapeInfo(), output.specialBuffer(), output.specialShapeInfo(), isNCHW), FLOAT_TYPES, FLOAT_TYPES);
-    NDArray::registerSpecialUse({&output}, {&input, &bias});
 
+    if (input.rankOf() == 2 && bias.rankOf() == 1 && input.ordering() == 'c' && output.ordering() == 'c' && input.ews() == 1 && bias.ews() == 1 && input.sizeAt(1) == bias.sizeAt(0)) {
+        BUILD_DOUBLE_SELECTOR(input.dataType(), bias.dataType(), addBias2DCudaLauncher,
+                              (block.launchContext()->getCudaStream(), input.getSpecialBuffer(), bias.getSpecialBuffer(), output.specialBuffer(), input.sizeAt(0), bias.sizeAt(0)),
+                              FLOAT_TYPES, FLOAT_TYPES);
+    } else {
+        // default case
+        const int threadsPerBlock = MAX_NUM_THREADS / 2;
+        const int blocksPerGrid = (input.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
+        const int sharedMem = input.rankOf() * sizeof(Nd4jLong) * threadsPerBlock + 128;
+
+
+        BUILD_DOUBLE_SELECTOR(input.dataType(), bias.dataType(), addBiasCudaLauncher,
+                              (blocksPerGrid, threadsPerBlock, sharedMem, block.launchContext()->getCudaStream(), input.getSpecialBuffer(), input.getSpecialShapeInfo(), bias.getSpecialBuffer(), bias.getSpecialShapeInfo(), output.specialBuffer(), output.specialShapeInfo(), isNCHW),
+                              FLOAT_TYPES, FLOAT_TYPES);
+    }
+    NDArray::registerSpecialUse({&output}, {&input, &bias});
     manager.synchronize();
 }