diff --git a/comfy/ldm/pixeldit/pid.py b/comfy/ldm/pixeldit/pid.py
index 21b73907a..db3653e7f 100644
--- a/comfy/ldm/pixeldit/pid.py
+++ b/comfy/ldm/pixeldit/pid.py
@@ -3,16 +3,24 @@ directly to a 4x-upscaled image in 4 distilled flow-matching steps. PixDiT_T2I
 body + LQ projection branch injected before each MMDiT patch block.
 """
 
+import logging
 from typing import List
 
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
+import comfy.model_management
+
 from .model import PixDiT_T2I
 from .modules import precompute_freqs_cis_2d
 
 
+# Warn at most once per process when the ROCm/AOTriton attention path returns
+# non-finite values that the guard below sanitizes (see ComfyUI #14249).
+_PID_AMD_NONFINITE_WARNED = False
+
+
 class SigmaAwareGatePerTokenPerDim(nn.Module):
     """gate = sigmoid(content_proj(cat[x, lq]) - exp(log_alpha) * sigma); out = x + gate * lq.
 
@@ -217,7 +225,7 @@ class PidNet(PixDiT_T2I):
 
         lq_features = self.lq_proj(lq_latent=lq_latent.to(x), target_pH=Hs, target_pW=Ws)
 
-        return super()._forward(
+        out = super()._forward(
             x, timesteps,
             context=context, attention_mask=attention_mask,
             transformer_options=transformer_options,
@@ -225,3 +233,15 @@ class PidNet(PixDiT_T2I):
             pid_degrade_sigma=degrade_sigma,
             **kwargs,
         )
+        if comfy.model_management.is_amd() and out.is_floating_point() and out.dtype in (torch.float16, torch.bfloat16) and not torch.isfinite(out).all():
+            global _PID_AMD_NONFINITE_WARNED
+            if not _PID_AMD_NONFINITE_WARNED:
+                logging.warning(
+                    "PiD produced non-finite output on AMD; sanitizing NaN/Inf so the "
+                    "decoded image stays usable. This is a known ROCm/AOTriton attention "
+                    "miscompilation on gfx11xx (ComfyUI #14249); for an unaffected run, "
+                    "launch with --use-split-cross-attention."
+                )
+                _PID_AMD_NONFINITE_WARNED = True
+            out = torch.nan_to_num(out, nan=0.0, posinf=65504.0, neginf=-65504.0)
+        return out