diff --git a/mlx_video/convert.py b/mlx_video/convert.py
index cbefd68..de9f01d 100644
--- a/mlx_video/convert.py
+++ b/mlx_video/convert.py
@@ -595,18 +595,15 @@ def convert(
 def save_weights(path: Path, weights: Dict[str, mx.array]) -> None:
     """Save weights in safetensors format.
 
+    Uses mx.save_safetensors to preserve exact dtype (especially bfloat16).
+    Converting through numpy loses bfloat16 fidelity since numpy lacks native
+    bfloat16 support.
+
     Args:
         path: Output directory
         weights: Dictionary of weights
     """
-    from safetensors.numpy import save_file
-    import numpy as np
-
-    # Convert to numpy for safetensors
-    np_weights = {k: np.array(v) for k, v in weights.items()}
-
-    # Save to file
-    save_file(np_weights, path / "model.safetensors")
+    mx.save_safetensors(str(path / "model.safetensors"), weights)
 
 
 def load_model(
diff --git a/tests/test_rope.py b/tests/test_rope.py
index f64a0c2..7406cf2 100644
--- a/tests/test_rope.py
+++ b/tests/test_rope.py
@@ -87,7 +87,7 @@ def _numpy_reference_rope(positions_np, dim, theta, max_pos, num_heads):
         cos_ref = np.concatenate([np.ones((*cos_ref.shape[:-1], pad_size)), cos_ref], axis=-1)
         sin_ref = np.concatenate([np.zeros((*sin_ref.shape[:-1], pad_size)), sin_ref], axis=-1)
 
-    B, T, F = cos_ref.shape
+    B, T, _ = cos_ref.shape
     dim_per_head = dim // num_heads
     cos_ref = cos_ref.reshape(B, T, num_heads, dim_per_head // 2).transpose(0, 2, 1, 3)
     sin_ref = sin_ref.reshape(B, T, num_heads, dim_per_head // 2).transpose(0, 2, 1, 3)