diff --git a/nodes.py b/nodes.py
index 2d81d76..bd4c79c 100644
--- a/nodes.py
+++ b/nodes.py
@@ -93,9 +93,12 @@ class CogVideoXPABConfig(PABConfig):
         spatial_broadcast: bool = True,
         spatial_threshold: list = [100, 850],
         spatial_range: int = 2,
-        temporal_broadcast: bool = True,
+        temporal_broadcast: bool = False,
         temporal_threshold: list = [100, 850],
-        temporal_range: int = 2,
+        temporal_range: int = 4,
+        cross_broadcast: bool = False,
+        cross_threshold: list = [100, 850],
+        cross_range: int = 6,
     ):
         super().__init__(
             steps=steps,
@@ -104,7 +107,10 @@ class CogVideoXPABConfig(PABConfig):
             spatial_range=spatial_range,
             temporal_broadcast=temporal_broadcast,
             temporal_threshold=temporal_threshold,
-            temporal_range=temporal_range
+            temporal_range=temporal_range,
+            cross_broadcast=cross_broadcast,
+            cross_threshold=cross_threshold,
+            cross_range=cross_range
 
         )
 
@@ -121,7 +127,12 @@ class CogVideoPABConfig:
             "temporal_broadcast": ("BOOLEAN", {"default": False, "tooltip": "Enable Temporal PAB"}),
             "temporal_threshold_start": ("INT", {"default": 850, "min": 0, "max": 1000, "tooltip": "PAB Start Timestep"} ),
             "temporal_threshold_end": ("INT", {"default": 100, "min": 0, "max": 1000, "tooltip": "PAB End Timestep"} ),
-            "temporal_range": ("INT", {"default": 2, "min": 0, "max": 10, "tooltip": "Broadcast timesteps range"} ),
+            "temporal_range": ("INT", {"default": 4, "min": 0, "max": 10, "tooltip": "Broadcast timesteps range"} ),
+            "cross_broadcast": ("BOOLEAN", {"default": False, "tooltip": "Enable Cross Attention PAB"}),
+            "cross_threshold_start": ("INT", {"default": 850, "min": 0, "max": 1000, "tooltip": "PAB Start Timestep"} ),
+            "cross_threshold_end": ("INT", {"default": 100, "min": 0, "max": 1000, "tooltip": "PAB End Timestep"} ),
+            "cross_range": ("INT", {"default": 6, "min": 0, "max": 10, "tooltip": "Broadcast timesteps range"} ),
+
             "steps": ("INT", {"default": 50, "min": 0, "max": 1000, "tooltip": "Steps"} ),
             }
         }
@@ -133,8 +144,10 @@ class CogVideoPABConfig:
     DESCRIPTION = "EXPERIMENTAL:Pyramid Attention Broadcast (PAB) speeds up inference by mitigating redundant attention computation"
 
     def config(self, spatial_broadcast, spatial_threshold_start, spatial_threshold_end, spatial_range, 
-               temporal_broadcast, temporal_threshold_start, temporal_threshold_end, temporal_range, steps):
+               temporal_broadcast, temporal_threshold_start, temporal_threshold_end, temporal_range, 
+               cross_broadcast, cross_threshold_start, cross_threshold_end, cross_range, steps):
         
+        #os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
         pab_config = CogVideoXPABConfig(
             steps=steps, 
             spatial_broadcast=spatial_broadcast, 
@@ -142,7 +155,10 @@ class CogVideoPABConfig:
             spatial_range=spatial_range,
             temporal_broadcast=temporal_broadcast,
             temporal_threshold=[temporal_threshold_end, temporal_threshold_start],
-            temporal_range=temporal_range
+            temporal_range=temporal_range,
+            cross_broadcast=cross_broadcast,
+            cross_threshold=[cross_threshold_end, cross_threshold_start],
+            cross_range=cross_range
             )
 
         return (pab_config, )
@@ -311,6 +327,9 @@ class DownloadAndLoadCogVideoGGUFModel:
             "load_device": (["main_device", "offload_device"], {"default": "main_device"}),
             "enable_sequential_cpu_offload": ("BOOLEAN", {"default": False, "tooltip": "significantly reducing memory usage and slows down the inference"}),
             },
+            "optional": {
+                "pab_config": ("PAB_CONFIG", {"default": None}),
+            }
         }
 
     RETURN_TYPES = ("COGVIDEOPIPE",)
@@ -318,7 +337,7 @@ class DownloadAndLoadCogVideoGGUFModel:
     FUNCTION = "loadmodel"
     CATEGORY = "CogVideoWrapper"
 
-    def loadmodel(self, model, vae_precision, fp8_fastmode, load_device, enable_sequential_cpu_offload):
+    def loadmodel(self, model, vae_precision, fp8_fastmode, load_device, enable_sequential_cpu_offload, pab_config=None):
         device = mm.get_torch_device()
         offload_device = mm.unet_offload_device()
         mm.soft_empty_cache()
@@ -370,7 +389,10 @@ class DownloadAndLoadCogVideoGGUFModel:
                 transformer = CogVideoXTransformer3DModel.from_config(transformer_config)
             else:
                 transformer_config["in_channels"] = 16
-                transformer = CogVideoXTransformer3DModel.from_config(transformer_config)
+                if pab_config is not None:
+                    transformer = CogVideoXTransformer3DModelPAB.from_config(transformer_config)
+                else:
+                    transformer = CogVideoXTransformer3DModel.from_config(transformer_config)
 
             if "2b" in model:
                 for name, param in transformer.named_parameters():
@@ -420,7 +442,7 @@ class DownloadAndLoadCogVideoGGUFModel:
         else:
             vae = AutoencoderKLCogVideoX.from_config(vae_config).to(vae_dtype).to(offload_device)
             vae.load_state_dict(vae_sd)
-            pipe = CogVideoXPipeline(vae, transformer, scheduler)
+            pipe = CogVideoXPipeline(vae, transformer, scheduler, pab_config=pab_config)
 
         # compilation
         # if compile == "torch":