diff --git a/server/voice_changer/RVC/inferencer/RVCInferencerv2.py b/server/voice_changer/RVC/inferencer/RVCInferencerv2.py
index 3391b90c2..9de9f1fd3 100644
--- a/server/voice_changer/RVC/inferencer/RVCInferencerv2.py
+++ b/server/voice_changer/RVC/inferencer/RVCInferencerv2.py
@@ -37,7 +37,7 @@ def loadModel(self, file: str, gpu: int):
                 model = model.eval()
                 self.use_jit = True
             else:
-                model = torch.jit.freeze(torch.jit.script(model.eval()))
+                model = torch.jit.optimize_for_inference(torch.jit.script(model.eval()), other_methods=['infer'])
                 torch.jit.save(model, jit_file)
                 self.use_jit = False
         else:
diff --git a/server/voice_changer/RVC/inferencer/RVCInferencerv2Nono.py b/server/voice_changer/RVC/inferencer/RVCInferencerv2Nono.py
index 075582f74..fe8c89350 100644
--- a/server/voice_changer/RVC/inferencer/RVCInferencerv2Nono.py
+++ b/server/voice_changer/RVC/inferencer/RVCInferencerv2Nono.py
@@ -37,7 +37,7 @@ def loadModel(self, file: str, gpu: int):
                 model = model.eval()
                 self.use_jit = True
             else:
-                model = torch.jit.freeze(torch.jit.script(model.eval()))
+                model = torch.jit.optimize_for_inference(torch.jit.script(model.eval()), other_methods=['infer'])
                 torch.jit.save(model, jit_file)
                 self.use_jit = False
         else:
diff --git a/server/voice_changer/common/rmvpe/rmvpe.py b/server/voice_changer/common/rmvpe/rmvpe.py
index d51f6e494..11b73f859 100644
--- a/server/voice_changer/common/rmvpe/rmvpe.py
+++ b/server/voice_changer/common/rmvpe/rmvpe.py
@@ -355,7 +355,7 @@ def __init__(self, model_path: str, is_half: bool, device: torch.device | str =
                 model = model.eval()
                 self.use_jit = True
             else:
-                model = torch.jit.freeze(torch.jit.script(model.eval()))
+                model = torch.jit.optimize_for_inference(torch.jit.script(model.eval()))
                 torch.jit.save(model, jit_file)
                 self.use_jit = False
         else: