diff --git a/nncf/quantization/algorithms/weight_compression/algorithm.py b/nncf/quantization/algorithms/weight_compression/algorithm.py
index 1d0da998605..0190de36471 100644
--- a/nncf/quantization/algorithms/weight_compression/algorithm.py
+++ b/nncf/quantization/algorithms/weight_compression/algorithm.py
@@ -43,7 +43,6 @@
 from nncf.scopes import IgnoredScope
 from nncf.scopes import get_ignored_node_names_from_ignored_scope
 from nncf.tensor import Tensor
-from nncf.tensor.definitions import TensorDataType
 
 TModel = TypeVar("TModel")
 TTensor = TypeVar("TTensor")
@@ -322,21 +321,6 @@ def _get_bitwidth_distribution_str(
         pretty_string = f"Statistics of the bitwidth distribution:\n{table}"
         return pretty_string
 
-    @staticmethod
-    def _is_float(dtype):
-        """
-        Check if the given data type is a floating-point type.
-
-        :param dtype: The data type to check.
-        :return: True if the data type is one of the floating-point types, False otherwise.
-        """
-        return dtype in [
-            TensorDataType.float16,
-            TensorDataType.bfloat16,
-            TensorDataType.float32,
-            TensorDataType.float64,
-        ]
-
     def _get_ignored_scope_weight_statistics(self, model: TModel, graph: NNCFGraph) -> List[int]:
         """
         Collect the weight statistics for nodes in the ignored scope.
@@ -359,7 +343,7 @@ def _get_ignored_scope_weight_statistics(self, model: TModel, graph: NNCFGraph)
                 continue
             for _, weight_port_id in self._backend_entity.get_weight_names_and_port_ids(node, graph):
                 weight_dtype = self._backend_entity.get_weight_dtype(node, weight_port_id, model, graph)
-                if not WeightCompression._is_float(weight_dtype):
+                if weight_dtype.is_float():
                     continue
                 weight_shape = self._backend_entity.get_weight_shape(node, weight_port_id, graph)
                 weight_size = reduce(operator.mul, weight_shape, 1)
@@ -391,7 +375,7 @@ def apply(
                     continue
 
                 weight_dtype = self._backend_entity.get_weight_dtype(node, weight_port_id, model, graph)
-                if not WeightCompression._is_float(weight_dtype):
+                if not weight_dtype.is_float():
                     continue
                 weight_shape = self._backend_entity.get_weight_shape(node, weight_port_id, graph)
                 weight_size = reduce(operator.mul, weight_shape, 1)
diff --git a/nncf/tensor/definitions.py b/nncf/tensor/definitions.py
index 447a6dd8bb5..2c0ac24f8ae 100644
--- a/nncf/tensor/definitions.py
+++ b/nncf/tensor/definitions.py
@@ -25,7 +25,7 @@ class TensorBackendType(Enum):
 
 class TensorDataType(Enum):
     """
-    Enum representing the different tensor data types.
+    The class represents the different tensor data types.
     """
 
     float16 = auto()
@@ -37,6 +37,12 @@ class TensorDataType(Enum):
     int64 = auto()
     uint8 = auto()
 
+    def is_float(self):
+        """
+        :return: True if the tensor data type is a floating-point type, else False.
+        """
+        return self in [TensorDataType.float16, TensorDataType.bfloat16, TensorDataType.float32, TensorDataType.float64]
+
 
 class TensorDeviceType(Enum):
     """