diff --git a/comfy/sd.py b/comfy/sd.py
index 85821120..3919f4bf 100644
--- a/comfy/sd.py
+++ b/comfy/sd.py
@@ -600,7 +600,7 @@ def load_unet(unet_path):
         raise RuntimeError("ERROR: Could not detect model type of: {}".format(unet_path))
     return model
 
-def save_checkpoint(output_path, model, clip=None, vae=None, clip_vision=None, metadata=None):
+def save_checkpoint(output_path, model, clip=None, vae=None, clip_vision=None, metadata=None, extra_keys={}):
     clip_sd = None
     load_models = [model]
     if clip is not None:
@@ -610,4 +610,7 @@ def save_checkpoint(output_path, model, clip=None, vae=None, clip_vision=None, m
     model_management.load_models_gpu(load_models)
     clip_vision_sd = clip_vision.get_sd() if clip_vision is not None else None
     sd = model.model.state_dict_for_saving(clip_sd, vae.get_sd(), clip_vision_sd)
+    for k in extra_keys:
+        sd[k] = extra_keys[k]
+
     comfy.utils.save_torch_file(sd, output_path, metadata=metadata)
diff --git a/comfy_extras/nodes_model_merging.py b/comfy_extras/nodes_model_merging.py
index a25b73ca..2a431f65 100644
--- a/comfy_extras/nodes_model_merging.py
+++ b/comfy_extras/nodes_model_merging.py
@@ -2,7 +2,9 @@ import comfy.sd
 import comfy.utils
 import comfy.model_base
 import comfy.model_management
+import comfy.model_sampling
 
+import torch
 import folder_paths
 import json
 import os
@@ -189,6 +191,13 @@ def save_checkpoint(model, clip=None, vae=None, clip_vision=None, filename_prefi
     # "stable-diffusion-v2-768-v", "stable-diffusion-v2-unclip-l", "stable-diffusion-v2-unclip-h",
     # "v2-inpainting"
 
+    extra_keys = {}
+    model_sampling = model.get_model_object("model_sampling")
+    if isinstance(model_sampling, comfy.model_sampling.ModelSamplingContinuousEDM):
+        if isinstance(model_sampling, comfy.model_sampling.V_PREDICTION):
+            extra_keys["edm_vpred.sigma_max"] = torch.tensor(model_sampling.sigma_max).float()
+            extra_keys["edm_vpred.sigma_min"] = torch.tensor(model_sampling.sigma_min).float()
+
     if model.model.model_type == comfy.model_base.ModelType.EPS:
         metadata["modelspec.predict_key"] = "epsilon"
     elif model.model.model_type == comfy.model_base.ModelType.V_PREDICTION:
@@ -203,7 +212,7 @@ def save_checkpoint(model, clip=None, vae=None, clip_vision=None, filename_prefi
     output_checkpoint = f"{filename}_{counter:05}_.safetensors"
     output_checkpoint = os.path.join(full_output_folder, output_checkpoint)
 
-    comfy.sd.save_checkpoint(output_checkpoint, model, clip, vae, clip_vision, metadata=metadata)
+    comfy.sd.save_checkpoint(output_checkpoint, model, clip, vae, clip_vision, metadata=metadata, extra_keys=extra_keys)
 
 class CheckpointSave:
     def __init__(self):