diff --git a/concrete/quantization/post_training.py b/concrete/quantization/post_training.py
index f60fb8614..4736fcb1b 100644
--- a/concrete/quantization/post_training.py
+++ b/concrete/quantization/post_training.py
@@ -88,7 +88,12 @@ class PostTrainingAffineQuantization:
                 # Create a QuantizedLinear layer
                 q_weights = self.quant_params[f"{name}.weight"]
                 q_bias = self.quant_params[f"{name}.bias"]
-                q_layer = QuantizedLinear(self.n_bits, q_weights, q_bias)
+                # Check if layer is last layer from the model
+                if name == list(self.numpy_model.torch_model.named_children())[-1][0]:
+                    # If last layer, we can use 7 bits (maximum allowed) of precision.
+                    q_layer = QuantizedLinear(7, q_weights, q_bias)
+                else:
+                    q_layer = QuantizedLinear(self.n_bits, q_weights, q_bias)
                 # Calibrate and get new calibration_data for next layer/activation
                 calibration_data = self._calibrate_layers_activation(
                     name, q_layer, calibration_data