diff --git a/__init__.py b/__init__.py
index 53c313c..d543d60 100644
--- a/__init__.py
+++ b/__init__.py
@@ -224,6 +224,8 @@ from .wanvideo import (
     WanVideoSampler,
     WanVideoVACEEncode,
     WanVideoEncode,
+    LoadWanVideoClipTextEncoder,
+    WanVideoClipVisionEncode,
 )
 
 from .wrappers import (
@@ -373,6 +375,8 @@ wanvideo_nodes = {
     "WanVideoSamplerMultiGPU": WanVideoSampler,
     "WanVideoVACEEncodeMultiGPU": WanVideoVACEEncode,
     "WanVideoEncodeMultiGPU": WanVideoEncode,
+    "LoadWanVideoClipTextEncoderMultiGPU": LoadWanVideoClipTextEncoder,
+    "WanVideoClipVisionEncodeMultiGPU": WanVideoClipVisionEncode,
 }
 register_and_count(["ComfyUI-WanVideoWrapper", "comfyui-wanvideowrapper"], wanvideo_nodes)
 
diff --git a/wanvideo.py b/wanvideo.py
index f4164dd..a89cff1 100644
--- a/wanvideo.py
+++ b/wanvideo.py
@@ -261,6 +261,44 @@ class LoadWanVideoT5TextEncoder:
 
         return text_encoder, device
 
+class LoadWanVideoClipTextEncoder:
+    @classmethod
+    def INPUT_TYPES(s):
+        devices = get_device_list()
+        default_device = devices[1] if len(devices) > 1 else devices[0]
+        return {
+            "required": {
+                "model_name": (folder_paths.get_filename_list("clip_vision") + folder_paths.get_filename_list("text_encoders"), {"tooltip": "These models are loaded from 'ComfyUI/models/clip_vision'"}),
+                 "precision": (["fp16", "fp32", "bf16"],
+                    {"default": "fp16"}
+                ),
+            },
+            "optional": {
+                "device": (devices, {"default": default_device}),
+            }
+        }
+
+    RETURN_TYPES = ("CLIP_VISION", "MULTIGPUDEVICE")
+    RETURN_NAMES = ("wan_clip_vision", "load_device")
+    FUNCTION = "loadmodel"
+    CATEGORY = "multigpu/WanVideoWrapper"
+    DESCRIPTION = "Loads Wan clip_vision model from 'ComfyUI/models/clip_vision'"
+
+    def loadmodel(self, model_name, precision, device=None):
+        from . import set_current_device
+
+        set_current_device(device)
+        
+        if device == "cpu":
+            load_device = "offload_device"
+        else:
+            load_device = "main_device"
+
+        original_loader = NODE_CLASS_MAPPINGS["LoadWanVideoClipTextEncoder"]()
+        clip_model = original_loader.loadmodel(model_name, precision, load_device)
+
+        return clip_model, device
+
 class WanVideoTextEncodeCached:
     @classmethod
     def INPUT_TYPES(s):
@@ -632,3 +670,45 @@ class WanVideoEncode:
             return original_encode.encode(vae[0], image, enable_vae_tiling, tile_x, tile_y, tile_stride_x, tile_stride_y, noise_aug_strength, latent_strength, mask)
         finally:
             encode_module.device = original_module_device
+
+class WanVideoClipVisionEncode:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+            "clip_vision": ("CLIP_VISION",),
+            "load_device": ("MULTIGPUDEVICE",),
+            "image_1": ("IMAGE", {"tooltip": "Image to encode"}),
+            "strength_1": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001, "tooltip": "Additional clip embed multiplier"}), 
+            "strength_2": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001, "tooltip": "Additional clip embed multiplier"}),
+            "crop": (["center", "disabled"], {"default": "center", "tooltip": "Crop image to 224x224 before encoding"}),
+            "combine_embeds": (["average", "sum", "concat", "batch"], {"default": "average", "tooltip": "Method to combine multiple clip embeds"}),
+            "force_offload": ("BOOLEAN", {"default": True}),
+            },
+            "optional": {
+                "image_2": ("IMAGE", ),
+                "negative_image": ("IMAGE", {"tooltip": "image to use for uncond"}),
+                "tiles": ("INT", {"default": 0, "min": 0, "max": 16, "step": 2, "tooltip": "Use matteo's tiled image encoding for improved accuracy"}),
+                "ratio": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Ratio of the tile average"}),
+            }
+        }
+
+    RETURN_TYPES = ("WANVIDIMAGE_CLIPEMBEDS",)
+    RETURN_NAMES = ("image_embeds",)
+    FUNCTION = "process"
+    CATEGORY = "multigpu/WanVideoWrapper"
+
+    def process(self, clip_vision, load_device, image_1, strength_1, strength_2, force_offload, crop, combine_embeds, image_2=None, negative_image=None, tiles=0, ratio=1.0):
+        from . import set_current_device
+
+        original_encode = NODE_CLASS_MAPPINGS["WanVideoClipVisionEncode"]()
+        encode_module = inspect.getmodule(original_encode)
+        original_module_device = encode_module.device
+
+        set_current_device(load_device)
+        compute_device_to_be_patched = mm.get_torch_device()
+        encode_module.device = compute_device_to_be_patched
+
+        try:
+            return original_encode.process(clip_vision[0], image_1, strength_1, strength_2, force_offload, crop, combine_embeds, image_2, negative_image, tiles, ratio)
+        finally:
+            encode_module.device = original_module_device