diff --git a/api/onnx_web/diffusers/load.py b/api/onnx_web/diffusers/load.py
index 36a35b7a..28bdac75 100644
--- a/api/onnx_web/diffusers/load.py
+++ b/api/onnx_web/diffusers/load.py
@@ -7,7 +7,12 @@ from optimum.onnxruntime import (  # ORTStableDiffusionXLInpaintPipeline,
     ORTStableDiffusionXLImg2ImgPipeline,
     ORTStableDiffusionXLPipeline,
 )
-from optimum.onnxruntime.modeling_diffusion import ORTModelTextEncoder, ORTModelUnet
+from optimum.onnxruntime.modeling_diffusion import (
+    ORTModelTextEncoder,
+    ORTModelUnet,
+    ORTModelVaeDecoder,
+    ORTModelVaeEncoder,
+)
 from transformers import CLIPTokenizer
 
 from ..constants import ONNX_MODEL
@@ -363,26 +368,40 @@ def load_pipeline(
                     sess_options=device.sess_options(),
                 )
             )
-        elif (
-            not params.is_xl() and path.exists(vae_decoder) and path.exists(vae_encoder)
-        ):
-            logger.debug("loading VAE decoder from %s", vae_decoder)
-            components["vae_decoder"] = OnnxRuntimeModel(
-                OnnxRuntimeModel.load_model(
+        elif path.exists(vae_decoder) and path.exists(vae_encoder):
+            if params.is_xl():
+                logger.debug("loading VAE decoder from %s", vae_decoder)
+                components["vae_decoder_session"] = OnnxRuntimeModel.load_model(
                     vae_decoder,
                     provider=device.ort_provider("vae"),
                     sess_options=device.sess_options(),
                 )
-            )
 
-            logger.debug("loading VAE encoder from %s", vae_encoder)
-            components["vae_encoder"] = OnnxRuntimeModel(
-                OnnxRuntimeModel.load_model(
+                logger.debug("loading VAE encoder from %s", vae_encoder)
+                components["vae_encoder_session"] = OnnxRuntimeModel.load_model(
                     vae_encoder,
                     provider=device.ort_provider("vae"),
                     sess_options=device.sess_options(),
                 )
-            )
+
+            else:
+                logger.debug("loading VAE decoder from %s", vae_decoder)
+                components["vae_decoder"] = OnnxRuntimeModel(
+                    OnnxRuntimeModel.load_model(
+                        vae_decoder,
+                        provider=device.ort_provider("vae"),
+                        sess_options=device.sess_options(),
+                    )
+                )
+
+                logger.debug("loading VAE encoder from %s", vae_encoder)
+                components["vae_encoder"] = OnnxRuntimeModel(
+                    OnnxRuntimeModel.load_model(
+                        vae_encoder,
+                        provider=device.ort_provider("vae"),
+                        sess_options=device.sess_options(),
+                    )
+                )
 
         # additional options for panorama pipeline
         if params.is_panorama():
@@ -402,33 +421,30 @@ def load_pipeline(
 
         # make sure XL models are actually being used
         if "text_encoder_session" in components:
-            logger.info(
-                "text encoder matches: %s, %s",
-                pipe.text_encoder.session == components["text_encoder_session"],
-                type(pipe.text_encoder),
-            )
             pipe.text_encoder = ORTModelTextEncoder(text_encoder_session, text_encoder)
 
         if "text_encoder_2_session" in components:
-            logger.info(
-                "text encoder 2 matches: %s, %s",
-                pipe.text_encoder_2.session == components["text_encoder_2_session"],
-                type(pipe.text_encoder_2),
-            )
             pipe.text_encoder_2 = ORTModelTextEncoder(
                 text_encoder_2_session, text_encoder_2
             )
 
         if "unet_session" in components:
-            logger.info(
-                "unet matches: %s, %s",
-                pipe.unet.session == components["unet_session"],
-                type(pipe.unet),
-            )
+            # unload old UNet first
             pipe.unet = None
             run_gc([device])
+            # load correct one
             pipe.unet = ORTModelUnet(unet_session, unet_model)
 
+        if "vae_decoder_session" in components:
+            pipe.vae_decoder = ORTModelVaeDecoder(
+                components["vae_decoder_session"], vae_decoder
+            )
+
+        if "vae_encoder_session" in components:
+            pipe.vae_encoder = ORTModelVaeEncoder(
+                components["vae_encoder_session"], vae_encoder
+            )
+
         if not server.show_progress:
             pipe.set_progress_bar_config(disable=True)