diff --git a/torchao/dtypes/floatx/float8_layout.py b/torchao/dtypes/floatx/float8_layout.py
index 5a7e1924b3..656ebb61ae 100644
--- a/torchao/dtypes/floatx/float8_layout.py
+++ b/torchao/dtypes/floatx/float8_layout.py
@@ -253,6 +253,7 @@ def _linear_fp8_act_fp8_weight_impl(
 ):
     """Implements matmul between FP8 input and FP8 weight with compute using _scaled_mm"""
     scaled_mm_config = weight_tensor._layout.mm_config
+    assert scaled_mm_config is not None
     out_shape = get_out_shape(input_tensor.shape, weight_tensor.shape)
 
     # Weight tensor preprocessing
diff --git a/tutorials/calibration_flow/static_quant.py b/tutorials/calibration_flow/static_quant.py
index 4b7dfe405f..fd24a71189 100644
--- a/tutorials/calibration_flow/static_quant.py
+++ b/tutorials/calibration_flow/static_quant.py
@@ -163,12 +163,13 @@ def __init__(
                 weight, weight_scale, weight_zero_point, block_size, self.target_dtype
             )
         elif self.target_dtype == torch.float8_e4m3fn:
+            mm_config = Float8MMConfig(use_fast_accum=True)
             self.qweight = to_affine_quantized_floatx_static(
                 weight,
                 weight_scale,
                 block_size,
                 target_dtype,
-                Float8Layout(mm_config=None),
+                Float8Layout(mm_config=mm_config),
             )
         else:
             raise ValueError(f"Unsupported target dtype {self.target_dtype}")