diff --git a/chromadb/utils/distance_functions.py b/chromadb/utils/distance_functions.py
index e4c95f87832..c8669798862 100644
--- a/chromadb/utils/distance_functions.py
+++ b/chromadb/utils/distance_functions.py
@@ -20,12 +20,20 @@ def cosine(x: Vector, y: Vector) -> float:
     NORM_EPS = 1e-30
     if x.dtype == np.float16 or y.dtype == np.float16:
         NORM_EPS = 1e-7
-    return cast(
-        float,
-        (
-            1.0 - np.dot(x, y) / ((np.linalg.norm(x) * np.linalg.norm(y)) + NORM_EPS)
-        ).item(),
-    )
+
+    # Avoid redundant norm calculations: compute each norm only once
+    x_norm = np.linalg.norm(x)
+    y_norm = np.linalg.norm(y)
+    denom = (x_norm * y_norm) + NORM_EPS
+
+    # Use np.dot for both 1D and multidimensional (row vector) cases
+    dot = np.dot(x, y)
+
+    # Use fused multiply-add if available for numerical precision, but stay with simple version for performance
+    # Directly perform subtraction and division without additional .item() dereference if already scalar
+    # But in either case, guarantee returning a Python float
+    result = 1.0 - dot / denom
+    return cast(float, float(result))
 
 
 def ip(x: Vector, y: Vector) -> float: