jaidaken/ComfyUI
1
0
Fork 0
Code Issues Pull Requests Actions 1 Packages Projects Releases Wiki Activity

Better chroma radiance and other models vram estimation. (#11278)

Browse Source
This commit is contained in:
comfyanonymous
2025-12-11 14:33:09 -08:00
committed by GitHub
parent ae65433a60
commit eeb020b9b7
1 changed files with 6 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
comfy/supported_models.py
View File

@@ -965,7 +965,7 @@ class CosmosT2IPredict2(supported_models_base.BASE):
def __init__(self, unet_config): def __init__(self, unet_config):
super().__init__(unet_config) super().__init__(unet_config)
self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.9 self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.95
def get_model(self, state_dict, prefix="", device=None): def get_model(self, state_dict, prefix="", device=None):
out = model_base.CosmosPredict2(self, device=device) out = model_base.CosmosPredict2(self, device=device)
@@ -1289,7 +1289,7 @@ class ChromaRadiance(Chroma):
latent_format = comfy.latent_formats.ChromaRadiance latent_format = comfy.latent_formats.ChromaRadiance
# Pixel-space model, no spatial compression for model input. # Pixel-space model, no spatial compression for model input.
memory_usage_factor = 0.038 memory_usage_factor = 0.044
def get_model(self, state_dict, prefix="", device=None): def get_model(self, state_dict, prefix="", device=None):
return model_base.ChromaRadiance(self, device=device) return model_base.ChromaRadiance(self, device=device)
@@ -1332,7 +1332,7 @@ class Omnigen2(supported_models_base.BASE):
"shift": 2.6, "shift": 2.6,
} }
memory_usage_factor = 1.65 #TODO memory_usage_factor = 1.95 #TODO
unet_extra_config = {} unet_extra_config = {}
latent_format = latent_formats.Flux latent_format = latent_formats.Flux
@@ -1397,7 +1397,7 @@ class HunyuanImage21(HunyuanVideo):
latent_format = latent_formats.HunyuanImage21 latent_format = latent_formats.HunyuanImage21
memory_usage_factor = 7.7 memory_usage_factor = 8.7
supported_inference_dtypes = [torch.bfloat16, torch.float32] supported_inference_dtypes = [torch.bfloat16, torch.float32]
@@ -1488,7 +1488,7 @@ class Kandinsky5(supported_models_base.BASE):
unet_extra_config = {} unet_extra_config = {}
latent_format = latent_formats.HunyuanVideo latent_format = latent_formats.HunyuanVideo
memory_usage_factor = 1.1 #TODO memory_usage_factor = 1.25 #TODO
supported_inference_dtypes = [torch.bfloat16, torch.float32] supported_inference_dtypes = [torch.bfloat16, torch.float32]
@@ -1517,7 +1517,7 @@ class Kandinsky5Image(Kandinsky5):
} }
latent_format = latent_formats.Flux latent_format = latent_formats.Flux
memory_usage_factor = 1.1 #TODO memory_usage_factor = 1.25 #TODO
def get_model(self, state_dict, prefix="", device=None): def get_model(self, state_dict, prefix="", device=None):
out = model_base.Kandinsky5Image(self, device=device) out = model_base.Kandinsky5Image(self, device=device)