diff --git a/ldm_patched/modules/model_base.py b/ldm_patched/modules/model_base.py
index 9e141294..614b0d47 100644
--- a/ldm_patched/modules/model_base.py
+++ b/ldm_patched/modules/model_base.py
@@ -6,6 +6,7 @@ import torch
 from ldm_patched.ldm.modules.diffusionmodules.openaimodel import UNetModel, Timestep
 from ldm_patched.ldm.modules.encoders.noise_aug_modules import CLIPEmbeddingNoiseAugmentation
 from ldm_patched.ldm.modules.diffusionmodules.upscaling import ImageConcatWithNoiseAugmentation
+import ldm_patched.ldm.modules.attention
 import ldm_patched.modules.model_management
 import ldm_patched.modules.conds
 import ldm_patched.modules.ops
@@ -209,17 +210,18 @@ class BaseModel(torch.nn.Module):
         self.inpaint_model = True
 
     def memory_required(self, input_shape):
+        area = input_shape[0] * input_shape[2] * input_shape[3]
+        dtype = self.manual_cast_dtype if self.manual_cast_dtype is not None else self.get_dtype()
+        dtype_size = ldm_patched.modules.model_management.dtype_size(dtype)
+
         if ldm_patched.modules.model_management.xformers_enabled() or ldm_patched.modules.model_management.pytorch_attention_flash_attention():
-            dtype = self.get_dtype()
-            if self.manual_cast_dtype is not None:
-                dtype = self.manual_cast_dtype
-            #TODO: this needs to be tweaked
-            area = input_shape[0] * input_shape[2] * input_shape[3]
-            return (area * ldm_patched.modules.model_management.dtype_size(dtype) / 50) * (1024 * 1024)
+            scaler = 1.25
         else:
-            #TODO: this formula might be too aggressive since I tweaked the sub-quad and split algorithms to use less memory.
-            area = input_shape[0] * input_shape[2] * input_shape[3]
-            return (((area * 0.6) / 0.9) + 1024) * (1024 * 1024)
+            scaler = 1.75
+            if ldm_patched.ldm.modules.attention._ATTN_PRECISION == "fp32":
+                dtype_size = 4
+
+        return scaler * area * dtype_size * 16384
 
 
 def unclip_adm(unclip_conditioning, device, noise_augmentor, noise_augment_merge=0.0, seed=None):