diff --git a/tests/diffusion/models/hunyuan_image3/test_hunyuan_image3_rgb.py b/tests/diffusion/models/hunyuan_image3/test_hunyuan_image3_rgb.py
new file mode 100644
index 000000000..5dcb682f4
--- /dev/null
+++ b/tests/diffusion/models/hunyuan_image3/test_hunyuan_image3_rgb.py
@@ -0,0 +1,54 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Tests for HunyuanImage3 AR image RGB conversion."""
+
+from types import SimpleNamespace
+
+import pytest
+import torch
+from PIL import Image
+
+from vllm_omni.model_executor.models.hunyuan_image3.hunyuan_image3 import (
+    HunyuanImage3Processor,
+)
+
+pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
+
+
+class _FixedResolutionGroup:
+    def get_target_size(self, width: int, height: int):
+        return width, height
+
+    def get_base_size_and_ratio_index(self, width: int, height: int):
+        return 1024, 0
+
+
+def test_ar_processor_uses_pil_rgb_conversion_for_rgba_images():
+    captured: dict[str, object] = {}
+
+    def fake_vit_processor(image: Image.Image):
+        captured["mode"] = image.mode
+        captured["pixel"] = image.getpixel((0, 0))
+        return {
+            "pixel_values": torch.zeros((1, 1, 3), dtype=torch.float32),
+            "pixel_attention_mask": torch.ones((1, 1), dtype=torch.bool),
+            "spatial_shapes": torch.tensor([[1, 1]], dtype=torch.long),
+        }
+
+    def fake_vae_processor(_image: Image.Image):
+        return torch.zeros((1, 3, 1, 1), dtype=torch.float32)
+
+    processor = object.__new__(HunyuanImage3Processor)
+    processor.hf_config = SimpleNamespace(
+        vit={"num_channels": 3},
+        vae_downsample_factor=(1, 1),
+        patch_size=1,
+    )
+    processor.reso_group = _FixedResolutionGroup()
+    processor.vision_encoder_processor = fake_vit_processor
+    processor.vae_processor = fake_vae_processor
+
+    processor.process_image(Image.new("RGBA", (1, 1), color=(255, 0, 0, 0)))
+
+    assert captured["mode"] == "RGB"
+    assert captured["pixel"] == (255, 0, 0)
diff --git a/vllm_omni/model_executor/models/hunyuan_image3/hunyuan_image3.py b/vllm_omni/model_executor/models/hunyuan_image3/hunyuan_image3.py
index 8c983cff1..f2321ba22 100755
--- a/vllm_omni/model_executor/models/hunyuan_image3/hunyuan_image3.py
+++ b/vllm_omni/model_executor/models/hunyuan_image3/hunyuan_image3.py
@@ -68,7 +68,6 @@ from vllm.model_executor.models.utils import (
     maybe_prefix,
 )
 from vllm.multimodal import MULTIMODAL_REGISTRY
-from vllm.multimodal.image import rgba_to_rgb
 from vllm.multimodal.inputs import (
     MultiModalFeatureSpec,
     MultiModalFieldConfig,
@@ -889,8 +888,8 @@ class HunyuanImage3Processor:
         for image in images:
             current_info = {}
 
-            if self.hf_config.vit["num_channels"] == 3 and image.mode == "RGBA":
-                image = rgba_to_rgb(image, (255, 255, 255))
+            if self.hf_config.vit["num_channels"] == 3 and image.mode != "RGB":
+                image = image.convert("RGB")
 
             # VIT processing
             vit_pixel_values = self.vision_encoder_processor(image)