diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index b811f33bf..6894c8ff9 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -283,6 +283,25 @@ class EmbeddingsWithFixes(torch.nn.Module):
         return torch.stack(vecs)
 
 
+class NNCF_T5DenseGatedActDense(torch.nn.Module): # forward can't find what self is without creating a class
+    def __init__(self, T5DenseGatedActDense):
+        super().__init__()
+        self.wi_0 = T5DenseGatedActDense.wi_0
+        self.wi_1 = T5DenseGatedActDense.wi_1
+        self.wo = T5DenseGatedActDense.wo
+        self.dropout = T5DenseGatedActDense.dropout
+        self.act = T5DenseGatedActDense.act
+
+    def forward(self, hidden_states):
+        hidden_gelu = self.act(self.wi_0(hidden_states))
+        hidden_linear = self.wi_1(hidden_states)
+        hidden_states = hidden_gelu * hidden_linear
+        hidden_states = self.dropout(hidden_states)
+        hidden_states = hidden_states.to(torch.float32) # this line needs to be forced to fp32
+        hidden_states = self.wo(hidden_states)
+        return hidden_states
+
+
 def add_circular_option_to_conv_2d():
     conv2d_constructor = torch.nn.Conv2d.__init__
 
diff --git a/modules/sd_models_compile.py b/modules/sd_models_compile.py
index c6006db25..f69b126b0 100644
--- a/modules/sd_models_compile.py
+++ b/modules/sd_models_compile.py
@@ -58,9 +58,23 @@ def apply_compile_to_model(sd_model, function, options, op=None):
                 sd_model.text_encoder = None
                 sd_model.text_encoder = sd_model.decoder_pipe.text_encoder = function(sd_model.decoder_pipe.text_encoder)
             else:
+                if op == "nncf" and sd_model.text_encoder.__class__.__name__ == "T5EncoderModel":
+                    from modules.sd_hijack import NNCF_T5DenseGatedActDense # T5DenseGatedActDense uses fp32
+                    for i in range(len(sd_model.text_encoder.encoder.block)):
+                        sd_model.text_encoder.encoder.block[i].layer[1].DenseReluDense = NNCF_T5DenseGatedActDense(
+                            sd_model.text_encoder.encoder.block[i].layer[1].DenseReluDense
+                        )
                 sd_model.text_encoder = function(sd_model.text_encoder)
         if hasattr(sd_model, 'text_encoder_2') and hasattr(sd_model.text_encoder_2, 'config'):
             sd_model.text_encoder_2 = function(sd_model.text_encoder_2)
+        if hasattr(sd_model, 'text_encoder_3') and hasattr(sd_model.text_encoder_2, 'config'):
+            if op == "nncf" and sd_model.text_encoder_3.__class__.__name__ == "T5EncoderModel":
+                from modules.sd_hijack import NNCF_T5DenseGatedActDense # T5DenseGatedActDense uses fp32
+                for i in range(len(sd_model.text_encoder_3.encoder.block)):
+                    sd_model.text_encoder_3.encoder.block[i].layer[1].DenseReluDense = NNCF_T5DenseGatedActDense(
+                        sd_model.text_encoder_3.encoder.block[i].layer[1].DenseReluDense
+                    )
+            sd_model.text_encoder_3 = function(sd_model.text_encoder_3)
         if hasattr(sd_model, 'prior_pipe') and hasattr(sd_model, 'prior_text_encoder'):
             sd_model.prior_text_encoder = None
             sd_model.prior_text_encoder = sd_model.prior_pipe.text_encoder = function(sd_model.prior_pipe.text_encoder)