diff --git a/comfy/model_detection.py b/comfy/model_detection.py
index c682c3e1..e3af422a 100644
--- a/comfy/model_detection.py
+++ b/comfy/model_detection.py
@@ -289,7 +289,13 @@ def unet_config_from_diffusers_unet(state_dict, dtype):
               'channel_mult': [1, 2, 4], 'transformer_depth_middle': -1, 'use_linear_in_transformer': True, 'context_dim': 2048, 'num_head_channels': 64,
               'use_temporal_attention': False, 'use_temporal_resblock': False}
 
-    supported_models = [SDXL, SDXL_refiner, SD21, SD15, SD21_uncliph, SD21_unclipl, SDXL_mid_cnet, SDXL_small_cnet, SDXL_diffusers_inpaint, SSD_1B]
+    Segmind_Vega = {'use_checkpoint': False, 'image_size': 32, 'out_channels': 4, 'use_spatial_transformer': True, 'legacy': False,
+              'num_classes': 'sequential', 'adm_in_channels': 2816, 'dtype': dtype, 'in_channels': 4, 'model_channels': 320,
+              'num_res_blocks': [2, 2, 2], 'transformer_depth': [0, 0, 1, 1, 2, 2], 'transformer_depth_output': [0, 0, 0, 1, 1, 1, 2, 2, 2],
+              'channel_mult': [1, 2, 4], 'transformer_depth_middle': -1, 'use_linear_in_transformer': True, 'context_dim': 2048, 'num_head_channels': 64,
+              'use_temporal_attention': False, 'use_temporal_resblock': False}
+
+    supported_models = [SDXL, SDXL_refiner, SD21, SD15, SD21_uncliph, SD21_unclipl, SDXL_mid_cnet, SDXL_small_cnet, SDXL_diffusers_inpaint, SSD_1B, Segmind_Vega]
 
     for unet_config in supported_models:
         matches = True
diff --git a/comfy/supported_models.py b/comfy/supported_models.py
index 455323b9..2f2dee87 100644
--- a/comfy/supported_models.py
+++ b/comfy/supported_models.py
@@ -217,6 +217,16 @@ class SSD1B(SDXL):
         "use_temporal_attention": False,
     }
 
+class Segmind_Vega(SDXL):
+    unet_config = {
+        "model_channels": 320,
+        "use_linear_in_transformer": True,
+        "transformer_depth": [0, 0, 1, 1, 2, 2],
+        "context_dim": 2048,
+        "adm_in_channels": 2816,
+        "use_temporal_attention": False,
+    }
+
 class SVD_img2vid(supported_models_base.BASE):
     unet_config = {
         "model_channels": 320,
@@ -242,5 +252,5 @@ class SVD_img2vid(supported_models_base.BASE):
     def clip_target(self):
         return None
 
-models = [SD15, SD20, SD21UnclipL, SD21UnclipH, SDXLRefiner, SDXL, SSD1B]
+models = [SD15, SD20, SD21UnclipL, SD21UnclipH, SDXLRefiner, SDXL, SSD1B, Segmind_Vega]
 models += [SVD_img2vid]