diff --git a/comfy/ldm/flux/math.py b/comfy/ldm/flux/math.py
index 6d0aed827..891dea7dd 100644
--- a/comfy/ldm/flux/math.py
+++ b/comfy/ldm/flux/math.py
@@ -4,7 +4,7 @@ from torch import Tensor
 
 from comfy.ldm.modules.attention import optimized_attention
 import comfy.model_management
-import logging
+import comfy.quant_ops
 
 
 def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor, mask=None, transformer_options={}) -> Tensor:
@@ -44,21 +44,15 @@ def _apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor):
     return apply_rope1(xq, freqs_cis), apply_rope1(xk, freqs_cis)
 
 
-try:
-    import comfy.quant_ops
-    q_apply_rope = comfy.quant_ops.ck.apply_rope
-    q_apply_rope1 = comfy.quant_ops.ck.apply_rope1
-    def apply_rope(xq, xk, freqs_cis):
-        if comfy.model_management.in_training:
-            return _apply_rope(xq, xk, freqs_cis)
-        else:
-            return apply_rope1(xq, freqs_cis), apply_rope1(xk, freqs_cis)
-    def apply_rope1(x, freqs_cis):
-        if comfy.model_management.in_training:
-            return _apply_rope1(x, freqs_cis)
-        else:
-            return q_apply_rope1(x, freqs_cis)
-except:
-    logging.warning("No comfy kitchen, using old apply_rope functions.")
-    apply_rope = _apply_rope
-    apply_rope1 = _apply_rope1
+def apply_rope(xq, xk, freqs_cis):
+    if comfy.model_management.in_training:
+        return _apply_rope(xq, xk, freqs_cis)
+    else:
+        return comfy.quant_ops.ck.apply_rope(xq, xk, freqs_cis)
+
+
+def apply_rope1(x, freqs_cis):
+    if comfy.model_management.in_training:
+        return _apply_rope1(x, freqs_cis)
+    else:
+        return comfy.quant_ops.ck.apply_rope1(x, freqs_cis)
diff --git a/comfy/multigpu.py b/comfy/multigpu.py
index bb9d334d3..2b6d8260d 100644
--- a/comfy/multigpu.py
+++ b/comfy/multigpu.py
@@ -54,6 +54,8 @@ class MultiGPUThreadPool:
             try:
                 result = fn(*args, **kwargs)
                 result_q.put((result, None))
+            except comfy.model_management.InterruptProcessingException as e:
+                result_q.put((None, e))
             except Exception as e:
                 result_q.put((None, e))
 
diff --git a/comfy_extras/nodes_pid.py b/comfy_extras/nodes_pid.py
index 811b9ae8e..71855254e 100644
--- a/comfy_extras/nodes_pid.py
+++ b/comfy_extras/nodes_pid.py
@@ -21,8 +21,8 @@ class PiDConditioning(io.ComfyNode):
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Latent.Input("latent", tooltip="latent (from VAEEncode or a KSampler)."),
-                io.Combo.Input("latent_format", options=["flux", "sd3"], default="flux",
-                               tooltip="Flux1 and Flux2 latents auto-detected from channel dim, sd3 has to be selected manually."),
+                io.Combo.Input("latent_format", options=["flux", "sd3", "sdxl", "qwenimage"], default="flux",
+                               tooltip="Flux1 (16-ch) and Flux2 (128-ch) latents are auto-detected from channel dim under 'flux'. For SD3 (16-ch), SDXL (4-ch), or QwenImage (16-ch), select manually."),
                 io.Float.Input(
                     "degrade_sigma", default=0.0, min=0.0, max=1.0, step=0.01,
                     tooltip="0 = clean latent. Increase to denoise corrupted latent outputs.",
@@ -36,9 +36,17 @@ class PiDConditioning(io.ComfyNode):
         samples = latent["samples"]
         if latent_format == "flux":
             fmt_cls = comfy.latent_formats.Flux2 if samples.shape[1] == 128 else comfy.latent_formats.Flux
-        else:
+        elif latent_format == "sd3":
             fmt_cls = comfy.latent_formats.SD3
+        elif latent_format == "sdxl":
+            fmt_cls = comfy.latent_formats.SDXL
+        elif latent_format == "qwenimage":
+            fmt_cls = comfy.latent_formats.Wan21
+        else:
+            raise ValueError(f"Unknown latent_format: {latent_format}")
         lq_latent = fmt_cls().process_in(samples)
+        if lq_latent.ndim == 5:
+            lq_latent = lq_latent[:, :, 0]
         sigma_t = torch.tensor([float(degrade_sigma)], dtype=torch.float32)
         return io.NodeOutput(node_helpers.conditioning_set_values(
             positive, {"lq_latent": lq_latent, "degrade_sigma": sigma_t},
diff --git a/requirements.txt b/requirements.txt
index b09d31a8b..7dff9e3c3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,7 +23,7 @@ SQLAlchemy>=2.0.0
 filelock
 av>=16.0.0
 comfy-kitchen==0.2.10
-comfy-aimdo==0.4.7
+comfy-aimdo==0.4.8
 requests
 simpleeval>=1.0.0
 blake3