diff --git a/src/frontends/onnx/frontend/src/op/random_uniform.cpp b/src/frontends/onnx/frontend/src/op/random_uniform.cpp
index c1f89bc2049246..4090f5125b6925 100644
--- a/src/frontends/onnx/frontend/src/op/random_uniform.cpp
+++ b/src/frontends/onnx/frontend/src/op/random_uniform.cpp
@@ -25,20 +25,18 @@ ov::OutputVector random_uniform(const ov::frontend::onnx::Node& node) {
                                           static_cast<int64_t>(TensorProto_DataType::TensorProto_DataType_FLOAT));
     const auto high_const = node.get_attribute_as_constant<float>("high", 1.0f);
     const auto low_const = node.get_attribute_as_constant<float>("low", 0.0f);
-    const auto seed = node.get_attribute_value<float>("seed", 0.0f);
+    const auto seed = common::convert_float_seed(node.get_attribute_value<float>("seed", 0.0f));
     const auto target_shape_const = node.get_attribute_as_constant<std::vector<int64_t>>("shape");
 
     const auto target_type = common::get_ov_element_type(dtype);
     const uint64_t global_seed = 0;
-    // TODO: This multiplication leads to a mismatch in accuracy. Issue: 123003
-    const auto seed_uint64 = static_cast<uint64_t>(seed * 1000);
 
     return {std::make_shared<v8::RandomUniform>(target_shape_const,
                                                 low_const,
                                                 high_const,
                                                 target_type,
                                                 global_seed,
-                                                seed_uint64)};
+                                                seed)};
 }
 
 }  // namespace set_1
diff --git a/src/frontends/onnx/frontend/src/op/random_uniform_like.cpp b/src/frontends/onnx/frontend/src/op/random_uniform_like.cpp
index 917e6c6780edaa..e8c9093bdc85a6 100644
--- a/src/frontends/onnx/frontend/src/op/random_uniform_like.cpp
+++ b/src/frontends/onnx/frontend/src/op/random_uniform_like.cpp
@@ -33,17 +33,16 @@ ov::OutputVector random_uniform_like(const ov::frontend::onnx::Node& node) {
 
     const auto high_const = node.get_attribute_as_constant<float>("high", 1.0f);
     const auto low_const = node.get_attribute_as_constant<float>("low", 0.0f);
-    const auto seed = node.get_attribute_value<float>("seed", 0.f);
+    const auto seed = common::convert_float_seed(node.get_attribute_value<float>("seed", 0.f));
 
     const uint64_t global_seed = 0;
-    const auto seed_uint64 = static_cast<uint64_t>(seed * 1000);
 
     return {std::make_shared<v8::RandomUniform>(target_shape,
                                                 low_const,
                                                 high_const,
                                                 target_type,
                                                 global_seed,
-                                                seed_uint64)};
+                                                seed)};
 }
 
 }  // namespace set_1
diff --git a/src/frontends/onnx/tests/onnx_import.in.cpp b/src/frontends/onnx/tests/onnx_import.in.cpp
index e15e4e768b6505..b90baa2bbc4674 100644
--- a/src/frontends/onnx/tests/onnx_import.in.cpp
+++ b/src/frontends/onnx/tests/onnx_import.in.cpp
@@ -4949,7 +4949,7 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_model_random_uniform) {
     const auto model = convert_model("random_uniform.onnx");
 
     auto test_case = ov::test::TestCase(model, s_device);
-    test_case.add_expected_output<float>(Shape{2, 2}, {43.45518f, 48.67585f, 42.227386f, 40.86294f});
+    test_case.add_expected_output<float>(Shape{2, 2}, {43.70129f, 45.26042f, 43.48503f, 46.43743f});
     test_case.run();
 }
 
@@ -4958,7 +4958,7 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_model_random_uniform_like) {
 
     auto test_case = ov::test::TestCase(model, s_device);
     test_case.add_input<float>(Shape{2, 2}, {41, 42, 43, 44});
-    test_case.add_expected_output<float>(Shape{2, 2}, {43.45518f, 48.67585f, 42.227386f, 40.86294f});
+    test_case.add_expected_output<float>(Shape{2, 2}, {43.70129f, 45.26042f, 43.48503f, 46.43743f});
     test_case.run();
 }
 
@@ -4966,7 +4966,7 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_model_random_normal) {
     const auto model = convert_model("random_normal.onnx");
 
     auto test_case = ov::test::TestCase(model, s_device);
-    test_case.add_expected_output<float>(Shape{2, 2}, {83.052017f, 55.496368f, 119.31188f, -3.6946249f});
+    test_case.add_expected_output<float>(Shape{2, 2}, {30.357481f, 72.41268f, 12.999034f, 70.04985f});
     test_case.run();
 }
 
@@ -4975,7 +4975,7 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_model_random_normal_like) {
 
     auto test_case = ov::test::TestCase(model, s_device);
     test_case.add_input<float>(Shape{2, 2}, {0, 0, 0, 0});
-    test_case.add_expected_output<float>(Shape{2, 2}, {83.052017f, 55.496368f, 119.31188f, -3.6946249f});
+    test_case.add_expected_output<float>(Shape{2, 2}, {30.357481f, 72.41268f, 12.999034f, 70.04985f});
     test_case.run();
 }