diff --git a/tt_eager/tt_dnn/op_library/composite/composite_ops.cpp b/tt_eager/tt_dnn/op_library/composite/composite_ops.cpp
index 324fba24dc5..c87a6b1f2e6 100644
--- a/tt_eager/tt_dnn/op_library/composite/composite_ops.cpp
+++ b/tt_eager/tt_dnn/op_library/composite/composite_ops.cpp
@@ -1236,14 +1236,9 @@ Tensor outer(Tensor& a, Tensor& b, const MemoryConfig& output_mem_config) {
     return operation::decorate_as_composite(__func__, _outer)(a, b, output_mem_config);
 }
 
-// Gated Linear Unit activation: matmul(split[0],sigmoid(split[1]))
-Tensor _glu(
-    const Tensor& input_a,
-    int32_t dim /* = -1 */,
-    const MemoryConfig& output_mem_config /* = operation::DEFAULT_OUTPUT_MEMORY_CONFIG */) {
-    TT_ASSERT(dim == -1 || dim == 3, "last dim GLU only supported at this time ");
-    if (dim == -1)
-        dim = 3;
+std::vector<Tensor> split_tensor_for_glu(const Tensor& input_a, int32_t dim, const MemoryConfig& output_mem_config)
+{
+    std::vector<Tensor> t_split;
     Shape inshape = input_a.get_legacy_shape();
     TT_FATAL(((inshape[dim] / 2 )% TILE_WIDTH == 0),
                 "Split tensor dimension should be in full tile");
@@ -1256,8 +1251,24 @@ Tensor _glu(
     Tensor t_a = unpad(input_a, s_a, e_a, output_mem_config);
     Tensor t_b = unpad(input_a, s_b, e_b, output_mem_config);
 
-    Tensor sigmoid_b = sigmoid(t_b, output_mem_config);
-    Tensor glu_result = mul(t_a, sigmoid_b, std::nullopt, output_mem_config);
+    t_split.emplace_back(t_a);
+    t_split.emplace_back(t_b);
+
+    return t_split;
+}
+
+// Gated Linear Unit activation: matmul(split[0],sigmoid(split[1]))
+Tensor _glu(
+    const Tensor& input_a,
+    int32_t dim /* = -1 */,
+    const MemoryConfig& output_mem_config /* = operation::DEFAULT_OUTPUT_MEMORY_CONFIG */) {
+    TT_ASSERT(dim == -1 || dim == 3, "last dim GLU only supported at this time ");
+    if (dim == -1)
+        dim = 3;
+
+    std::vector<Tensor> ab = split_tensor_for_glu(input_a, dim, output_mem_config);
+    Tensor sigmoid_b = sigmoid(ab[1], output_mem_config);
+    Tensor glu_result = mul(ab[0], sigmoid_b, std::nullopt, output_mem_config);
     return glu_result;
 }
 Tensor glu(
@@ -1275,19 +1286,9 @@ Tensor _reglu(
     TT_ASSERT(dim == -1 || dim == 3, "last dim REGLU only supported at this time ");
     if (dim == -1)
         dim = 3;
-    Shape inshape = input_a.get_legacy_shape();
-    TT_FATAL(((inshape[dim] / 2 )% TILE_WIDTH == 0),
-                "Split tensor dimension should be in full tile");
-    Shape s_a = {0, 0, 0, 0};
-    Shape e_a = {inshape[0]-1, inshape[1]-1, inshape[2]-1, inshape[3]/2 - 1 };
-
-    Shape s_b = {0, 0, 0, inshape[3]/2 };
-    Shape e_b = {inshape[0]-1, inshape[1]-1, inshape[2]-1, inshape[3] - 1 };
-
-    Tensor t_a = unpad(input_a, s_a, e_a, output_mem_config);
-    Tensor t_b = unpad(input_a, s_b, e_b, output_mem_config);
-    Tensor relu_b = relu(t_b, output_mem_config);
-    Tensor reglu_result = mul(t_a, relu_b, std::nullopt, output_mem_config);
+    std::vector<Tensor> ab = split_tensor_for_glu(input_a, dim, output_mem_config);
+    Tensor relu_b = relu(ab[1], output_mem_config);
+    Tensor reglu_result = mul(ab[0], relu_b, std::nullopt, output_mem_config);
     return reglu_result;
 }
 Tensor reglu(
@@ -1305,20 +1306,12 @@ Tensor _geglu(
     TT_ASSERT(dim == -1 || dim == 3, "last dim GEGLU only supported at this time ");
     if (dim == -1)
         dim = 3;
-    Shape inshape = input_a.get_legacy_shape();
-    TT_FATAL(((inshape[dim] / 2 )% TILE_WIDTH == 0),
-                "Split tensor dimension should be in full tile");
-    Shape s_a = {0, 0, 0, 0};
-    Shape e_a = {inshape[0]-1, inshape[1]-1, inshape[2]-1, inshape[3]/2 - 1 };
 
-    Shape s_b = {0, 0, 0, inshape[3]/2 };
-    Shape e_b = {inshape[0]-1, inshape[1]-1, inshape[2]-1, inshape[3] - 1 };
+    std::vector<Tensor> ab = split_tensor_for_glu(input_a, dim, output_mem_config);
 
-    Tensor t_a = unpad(input_a, s_a, e_a, output_mem_config);
-    Tensor t_b = unpad(input_a, s_b, e_b, output_mem_config);
     constexpr bool fast_appx = true;
-    Tensor gelu_b = gelu(t_b, fast_appx, output_mem_config);
-    Tensor geglu_result = mul(t_a, gelu_b, std::nullopt, output_mem_config);
+    Tensor gelu_b = gelu(ab[1], fast_appx, output_mem_config);
+    Tensor geglu_result = mul(ab[0], gelu_b, std::nullopt, output_mem_config);
     return geglu_result;
 }
 Tensor geglu(
@@ -1336,20 +1329,11 @@ Tensor _swiglu(
     TT_ASSERT(dim == -1 || dim == 3, "last dim SWIGLU only supported at this time ");
     if (dim == -1)
         dim = 3;
-    Shape inshape = input_a.get_legacy_shape();
-    TT_FATAL(((inshape[dim] / 2 )% TILE_WIDTH == 0),
-                "Split tensor dimension should be in full tile");
-    Shape s_a = {0, 0, 0, 0};
-    Shape e_a = {inshape[0]-1, inshape[1]-1, inshape[2]-1, inshape[3]/2 - 1 };
-
-    Shape s_b = {0, 0, 0, inshape[3]/2 };
-    Shape e_b = {inshape[0]-1, inshape[1]-1, inshape[2]-1, inshape[3] - 1 };
 
-    Tensor t_a = unpad(input_a, s_a, e_a, output_mem_config);
-    Tensor t_b = unpad(input_a, s_b, e_b, output_mem_config);
+    std::vector<Tensor> ab = split_tensor_for_glu(input_a, dim, output_mem_config);
 
-    Tensor swish_b = swish(t_b, output_mem_config);
-    Tensor swiglu_result = mul(t_a, swish_b, std::nullopt, output_mem_config);
+    Tensor swish_b = swish(ab[1], output_mem_config);
+    Tensor swiglu_result = mul(ab[0], swish_b, std::nullopt, output_mem_config);
     return swiglu_result;
 }
 Tensor swiglu(