diff --git a/examples/offline_inference/text_to_image/text_to_image.py b/examples/offline_inference/text_to_image/text_to_image.py
index 81acebe00..03bdf7080 100644
--- a/examples/offline_inference/text_to_image/text_to_image.py
+++ b/examples/offline_inference/text_to_image/text_to_image.py
@@ -8,7 +8,9 @@ import time
 from pathlib import Path
 from typing import Any
 
+import numpy as np
 import torch
+from diffusers.utils import numpy_to_pil
 
 from vllm_omni.diffusion.data import logger
 from vllm_omni.diffusion.utils.image_output import extract_images_from_outputs
@@ -54,6 +56,17 @@ def parse_json_object(value: str, flag_name: str = "argument") -> dict[str, Any]
 parse_profiler_config = functools.partial(parse_json_object, flag_name="--profiler-config")
 
 
+def _normalize_images_for_save(images: list[Any]) -> list[Any]:
+    """Convert NumPy diffusion outputs to PIL images before saving."""
+    normalized = []
+    for image in images:
+        if isinstance(image, np.ndarray):
+            normalized.extend(numpy_to_pil(image))
+        else:
+            normalized.append(image)
+    return normalized
+
+
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(description="Generate an image with supported diffusion models.")
     parser.add_argument(
@@ -619,6 +632,7 @@ def main():
 
     if not images:
         raise ValueError("No images found in request_output")
+    images = _normalize_images_for_save(images)
 
     output_path = Path(args.output)
     output_path.parent.mkdir(parents=True, exist_ok=True)