diff --git a/src/plugins/intel_gpu/src/graph/program.cpp b/src/plugins/intel_gpu/src/graph/program.cpp
index 5f6df98ff83063..4b0cc049013ada 100644
--- a/src/plugins/intel_gpu/src/graph/program.cpp
+++ b/src/plugins/intel_gpu/src/graph/program.cpp
@@ -517,7 +517,10 @@ void program::init_graph() {
     apply_opt_pass<graph_initializations>();
 
     apply_opt_pass<mark_nodes>();
-
+    for (auto& node : processing_order) {
+        if (!node->is_type<data>())
+            node->get_output_layouts();
+    }
     // Perform initial shape_of subgraphs markup
     apply_opt_pass<mark_shape_of_subgraphs>();
 }
@@ -533,10 +536,6 @@ void program::pre_optimize_graph(bool is_internal) {
     processing_order.calculate_BFS_processing_order();  // this method makes sense only for OOOQ (out of order execution queue)
 
     bool output_size_handling_enabled = analyze_output_size_handling_need();
-    for (auto& node : processing_order) {
-        if (!node->is_type<data>())
-            node->get_output_layouts();
-    }
 
     bool optimize_data = _config.get_property(ov::intel_gpu::optimize_data);
     if (optimize_data) {
diff --git a/src/plugins/intel_gpu/src/plugin/ops/loop.cpp b/src/plugins/intel_gpu/src/plugin/ops/loop.cpp
index c5ae7bbdef56a8..bb11308064f7e7 100644
--- a/src/plugins/intel_gpu/src/plugin/ops/loop.cpp
+++ b/src/plugins/intel_gpu/src/plugin/ops/loop.cpp
@@ -30,8 +30,14 @@ namespace intel_gpu {
 template<class DATA_TYPE>
 static DATA_TYPE CreateScalarData(ProgramBuilder &p, const cldnn::primitive_id& id, ov::Shape& shape, cldnn::data_types dtype, int64_t num, int64_t rank) {
     auto mem = p.get_engine().allocate_memory({ shape, dtype, cldnn::format::get_default_format(rank) });
-    cldnn::mem_lock<int64_t> ptr{mem, p.get_engine().get_service_stream()};
-    *ptr.begin() = num;
+    if (dtype == cldnn::data_types::i32) {
+        cldnn::mem_lock<int32_t> ptr{mem, p.get_engine().get_service_stream()};
+        *ptr.begin() = static_cast<int32_t>(num);
+    } else {
+        cldnn::mem_lock<int64_t> ptr{mem, p.get_engine().get_service_stream()};
+        *ptr.begin() = num;
+    }
+
     return {id, mem};
 }
 
diff --git a/src/plugins/intel_gpu/tests/unit/passes/test_module_fusing_reorder.cpp b/src/plugins/intel_gpu/tests/unit/passes/test_module_fusing_reorder.cpp
index 5e36ae2ea4bdc0..55521484685f67 100644
--- a/src/plugins/intel_gpu/tests/unit/passes/test_module_fusing_reorder.cpp
+++ b/src/plugins/intel_gpu/tests/unit/passes/test_module_fusing_reorder.cpp
@@ -266,7 +266,7 @@ TEST_P(test_can_fuse_reorder_onednn, reorder_for_firstconv_onednn)
     layout conv_layout(p.input_data_type, p.output_format, p.out_shape, padding({0, }, 0));
     layout reorder_layout(p.output_data_type, p.output_format, p.out_shape, padding({0, }, 0));
     auto input = engine.allocate_memory({ p.input_data_type, p.input_format, p.in_shape });
-    auto weights = engine.allocate_memory({ p.input_data_type, p.input_format, p.weight_shape });
+    auto weights = engine.allocate_memory({ p.input_data_type, p.weights_format, p.weight_shape });
 
     topology.add(input_layout("input", input->get_layout()));
     topology.add(data("weights", weights));
@@ -298,9 +298,9 @@ TEST_P(test_can_fuse_reorder_onednn, reorder_for_firstconv_onednn)
 INSTANTIATE_TEST_SUITE_P(testing_can_fuse_reorder_first_conv, test_can_fuse_reorder_onednn,
                         ::testing::ValuesIn(std::vector<reorder_test_param>{
                                             reorder_test_param{format::bs_fs_yx_bsv8_fsv4, format::b_fs_yx_fsv32, data_types::f32, data_types::u8, {1, 3, 8, 8}, {1, 32, 8, 8}, {1, 3, 1, 1},
-                                                tensor{1}, tensor{0}, data_types::u8, format::goiyx, true},
+                                                tensor{1}, tensor{0}, data_types::u8, format::oiyx, true},
                                             reorder_test_param{format::bs_fs_yx_bsv8_fsv2, format::b_fs_yx_fsv16, data_types::f32, data_types::f16, {1, 3, 8, 8}, {1, 32, 8, 8}, {1, 3, 1, 1},
-                                                tensor{1}, tensor{0}, data_types::f16, format::goiyx, true},
+                                                tensor{1}, tensor{0}, data_types::f16, format::oiyx, true},
                                             }));
 
 class can_fuse_reorder : public ::testing::TestWithParam<std::tuple<data_types, format>> {};