diff --git a/api/onnx_web/convert/diffusion_original.py b/api/onnx_web/convert/diffusion_original.py
index 52d69960..b11d1458 100644
--- a/api/onnx_web/convert/diffusion_original.py
+++ b/api/onnx_web/convert/diffusion_original.py
@@ -1301,7 +1301,7 @@ def extract_checkpoint(
             converted_vae_checkpoint = convert_ldm_vae_checkpoint(checkpoint, vae_config)
         else:
             vae_file = os.path.join(ctx.model_path, vae_file)
-            logger.debug("loading custom VAE file: %s", vae_file)
+            logger.debug("loading custom VAE: %s", vae_file)
             vae_checkpoint = load_tensor(vae_file, map_location=map_location)
             converted_vae_checkpoint = convert_ldm_vae_checkpoint(vae_checkpoint, vae_config, first_stage=False)
 
diff --git a/api/onnx_web/convert/diffusion_stable.py b/api/onnx_web/convert/diffusion_stable.py
index 135de80a..b6dec0a1 100644
--- a/api/onnx_web/convert/diffusion_stable.py
+++ b/api/onnx_web/convert/diffusion_stable.py
@@ -17,6 +17,7 @@ from typing import Dict
 
 import torch
 from diffusers import (
+    AutoencoderKL,
     OnnxRuntimeModel,
     OnnxStableDiffusionPipeline,
     StableDiffusionPipeline,
@@ -71,6 +72,7 @@ def convert_diffusion_stable(
     name = model.get("name")
     source = source or model.get("source")
     single_vae = model.get("single_vae")
+    replace_vae = model.get("vae")
 
     dtype = torch.float16 if ctx.half else torch.float32
     dest_path = path.join(ctx.model_path, name)
@@ -177,6 +179,11 @@ def convert_diffusion_stable(
     )
     del pipeline.unet
 
+    if replace_vae is not None:
+        logger.debug("loading custom VAE: %s", replace_vae)
+        vae = AutoencoderKL.from_pretrained(replace_vae)
+        pipeline.vae = vae
+
     if single_vae:
         logger.debug("VAE config: %s", pipeline.vae.config)