diff --git a/auto_round/data_type/mxfp.py b/auto_round/data_type/mxfp.py
index 862ff0a9a..7959f6a8a 100644
--- a/auto_round/data_type/mxfp.py
+++ b/auto_round/data_type/mxfp.py
@@ -77,6 +77,12 @@ def quant_element(tensor, ebits, mbits, max_norm, mantissa_rounding="even"):
     return tensor
 
 
+def quant_element_ste(tensor, ebits, mbits, max_norm, mantissa_rounding="even"):
+    with torch.no_grad():
+        tensor_q = quant_element(tensor, ebits, mbits, max_norm, mantissa_rounding)
+    return (tensor_q - tensor).detach() + tensor
+
+
 def quant_mx(tensor, bits=4, group_size=-1, v=0, max_scale=1.0, mantissa_rounding="even", data_type="mx_fp", **kwargs):
     """Quantize the given tensor using the specified parameters.
 
@@ -120,7 +126,7 @@ def quant_mx(tensor, bits=4, group_size=-1, v=0, max_scale=1.0, mantissa_roundin
     scale = torch.pow(2, shared_exp)
     tensor = tensor / scale + v
     tensor = torch.clamp(tensor, min=-max_norm, max=max_norm)
-    tensor = quant_element(tensor, ebits, mbits, max_norm, mantissa_rounding)
+    tensor = quant_element_ste(tensor, ebits, mbits, max_norm, mantissa_rounding)
 
     tensor = tensor * scale
     tensor = revert_tensor_by_pad(tensor, orig_shape=orig_shape, pad_len=pad_len)
@@ -171,7 +177,7 @@ def quant_mx_rceil(
     scale = torch.pow(2, shared_exp)
     tensor = tensor / scale + v
     tensor = torch.clamp(tensor, min=-max_norm, max=max_norm)
-    tensor = quant_element(tensor, ebits, mbits, max_norm, mantissa_rounding)
+    tensor = quant_element_ste(tensor, ebits, mbits, max_norm, mantissa_rounding)
 
     tensor = tensor * scale
     tensor = revert_tensor_by_pad(tensor, orig_shape=orig_shape, pad_len=pad_len)