diff --git a/supervision/detection/utils/boxes.py b/supervision/detection/utils/boxes.py
index 44b78cba..01fcdc76 100644
--- a/supervision/detection/utils/boxes.py
+++ b/supervision/detection/utils/boxes.py
@@ -123,12 +123,13 @@ def denormalize_boxes(
         import numpy as np
         import supervision as sv
 
-        normalized_xyxy = np.array([
+        xyxy = np.array([
             [0.1, 0.2, 0.5, 0.6],
             [0.3, 0.4, 0.7, 0.8],
             [0.2, 0.1, 0.6, 0.5]
         ])
-        sv.denormalize_boxes(normalized_xyxy, (1280, 720))
+
+        sv.denormalize_boxes(xyxy, (1280, 720))
         # array([
         #     [128., 144., 640., 432.],
         #     [384., 288., 896., 576.],
@@ -140,14 +141,11 @@ def denormalize_boxes(
         import numpy as np
         import supervision as sv
 
-        normalized_xyxy = np.array([
+        xyxy = np.array([
             [256., 128., 768., 640.]
         ])
-        result = sv.denormalize_boxes(
-            normalized_xyxy,
-            (1280, 720),
-            normalization_factor=1024.0
-        )
+
+        sv.denormalize_boxes(xyxy, (1280, 720), normalization_factor=1024.0)
         # array([
         #     [320.,  90., 960., 450.]
         # ])
diff --git a/supervision/detection/vlm.py b/supervision/detection/vlm.py
index 71207554..2f9b60dd 100644
--- a/supervision/detection/vlm.py
+++ b/supervision/detection/vlm.py
@@ -538,7 +538,7 @@ def from_google_gemini_2_0(
         return np.empty((0, 4)), None, np.empty((0,), dtype=str)
 
     labels = []
-    boxes_list = []
+    xyxy = []
 
     for item in data:
         if "box_2d" not in item or "label" not in item:
@@ -546,18 +546,16 @@ def from_google_gemini_2_0(
         labels.append(item["label"])
         box = item["box_2d"]
         # Gemini bbox order is [y_min, x_min, y_max, x_max]
-        boxes_list.append(
-            denormalize_boxes(
-                np.array([box[1], box[0], box[3], box[2]]).astype(np.float64),
-                resolution_wh=(w, h),
-                normalization_factor=1000,
-            )
-        )
+        xyxy.append([box[1], box[0], box[3], box[2]])
 
-    if not boxes_list:
+    if len(xyxy) == 0:
         return np.empty((0, 4)), None, np.empty((0,), dtype=str)
 
-    xyxy = np.array(boxes_list)
+    xyxy = denormalize_boxes(
+        np.array(xyxy, dtype=np.float64),
+        resolution_wh=(w, h),
+        normalization_factor=1000,
+    )
     class_name = np.array(labels)
     class_id = None
 
@@ -649,10 +647,10 @@ def from_google_gemini_2_5(
         box = item["box_2d"]
         # Gemini bbox order is [y_min, x_min, y_max, x_max]
         absolute_bbox = denormalize_boxes(
-            np.array([box[1], box[0], box[3], box[2]]).astype(np.float64),
+            np.array([[box[1], box[0], box[3], box[2]]]).astype(np.float64),
             resolution_wh=(w, h),
             normalization_factor=1000,
-        )
+        )[0]
         boxes_list.append(absolute_bbox)
 
         if "mask" in item:
@@ -735,7 +733,7 @@ def from_google_gemini_2_5(
 def from_moondream(
     result: dict,
     resolution_wh: tuple[int, int],
-) -> tuple[np.ndarray]:
+) -> np.ndarray:
     """
     Parse and scale bounding boxes from moondream JSON output.
 
@@ -773,7 +771,7 @@ def from_moondream(
     if "objects" not in result or not isinstance(result["objects"], list):
         return np.empty((0, 4), dtype=float)
 
-    denormalize_xyxy = []
+    xyxy = []
 
     for item in result["objects"]:
         if not all(k in item for k in ["x_min", "y_min", "x_max", "y_max"]):
@@ -784,14 +782,12 @@ def from_moondream(
         x_max = item["x_max"]
         y_max = item["y_max"]
 
-        denormalize_xyxy.append(
-            denormalize_boxes(
-                np.array([x_min, y_min, x_max, y_max]).astype(np.float64),
-                resolution_wh=(w, h),
-            )
-        )
+        xyxy.append([x_min, y_min, x_max, y_max])
 
-    if not denormalize_xyxy:
+    if len(xyxy) == 0:
         return np.empty((0, 4))
 
-    return np.array(denormalize_xyxy, dtype=float)
+    return denormalize_boxes(
+        np.array(xyxy).astype(np.float64),
+        resolution_wh=(w, h),
+    )
diff --git a/test/detection/utils/test_boxes.py b/test/detection/utils/test_boxes.py
index 787c970f..66d0d999 100644
--- a/test/detection/utils/test_boxes.py
+++ b/test/detection/utils/test_boxes.py
@@ -150,7 +150,7 @@ def test_scale_boxes(
 
 
 @pytest.mark.parametrize(
-    "normalized_xyxy, resolution_wh, normalization_factor, expected_result, exception",
+    "xyxy, resolution_wh, normalization_factor, expected_result, exception",
     [
         (
             np.empty(shape=(0, 4)),