diff --git a/comfy/customzluda/zluda.py b/comfy/customzluda/zluda.py
index ecc72413c..97744a741 100644
--- a/comfy/customzluda/zluda.py
+++ b/comfy/customzluda/zluda.py
@@ -7,8 +7,9 @@ os.environ.pop("HIP_HOME", None)
 os.environ.pop("ROCM_VERSION", None)
 
 #triton fix?
-os.environ["FLASH_ATTENTION_TRITON_AMD_ENABLE"] = "TRUE"
-os.environ["FLASH_ATTENTION_TRITON_AMD_AUTOTUNE"] = "TRUE"
+# disabling flash-attention
+# os.environ["FLASH_ATTENTION_TRITON_AMD_ENABLE"] = "TRUE"
+# os.environ["FLASH_ATTENTION_TRITON_AMD_AUTOTUNE"] = "TRUE"
 os.environ["TRITON_DEBUG"] = "1"     # Verbose logging
 
 paths = os.environ["PATH"].split(";")
@@ -668,46 +669,46 @@ def do_hijack():
             triton.runtime.driver.active.utils.get_device_properties = patched_props
             print("  ::  Triton device properties configured")
 
-            # Flash Attention
-            flash_enabled = False
-            try:
-                from comfy.flash_attn_triton_amd import interface_fa
-                print("  ::  Flash attention components found")
+            # # Flash Attention
+            # flash_enabled = False
+            # try:
+                # from comfy.flash_attn_triton_amd import interface_fa
+                # print("  ::  Flash attention components found")
                 
-                original_sdpa = torch.nn.functional.scaled_dot_product_attention
+                # original_sdpa = torch.nn.functional.scaled_dot_product_attention
                 
-                def amd_flash_wrapper(query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False, scale=None):
-                    try:
-                        if (query.shape[-1] <= 128 and 
-                            attn_mask is None and # fix flash-attention error : "Flash attention error: Boolean value of Tensor with more than one value is ambiguous" 
-                            query.dtype != torch.float32):
-                            if scale is None:
-                                scale = query.shape[-1] ** -0.5
-                            return interface_fa.fwd(
-                                query.transpose(1, 2),
-                                key.transpose(1, 2),
-                                value.transpose(1, 2),
-                                None, None, dropout_p, scale,
-                                is_causal, -1, -1, 0.0, False, None
-                            )[0].transpose(1, 2)
-                    except Exception as e:
-                        print(f'  ::  Flash attention error: {str(e)}')
-                    return original_sdpa(query=query, key=key, value=value, attn_mask=attn_mask, dropout_p=dropout_p, is_causal=is_causal, scale=scale)
+                # def amd_flash_wrapper(query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False, scale=None):
+                    # try:
+                        # if (query.shape[-1] <= 128 and 
+                            # attn_mask is None and # fix flash-attention error : "Flash attention error: Boolean value of Tensor with more than one value is ambiguous" 
+                            # query.dtype != torch.float32):
+                            # if scale is None:
+                                # scale = query.shape[-1] ** -0.5
+                            # return interface_fa.fwd(
+                                # query.transpose(1, 2),
+                                # key.transpose(1, 2),
+                                # value.transpose(1, 2),
+                                # None, None, dropout_p, scale,
+                                # is_causal, -1, -1, 0.0, False, None
+                            # )[0].transpose(1, 2)
+                    # except Exception as e:
+                        # print(f'  ::  Flash attention error: {str(e)}')
+                    # return original_sdpa(query=query, key=key, value=value, attn_mask=attn_mask, dropout_p=dropout_p, is_causal=is_causal, scale=scale)
                 
-                torch.nn.functional.scaled_dot_product_attention = amd_flash_wrapper
-                flash_enabled = True
-                print("  ::  AMD flash attention enabled successfully")
+                # torch.nn.functional.scaled_dot_product_attention = amd_flash_wrapper
+                # flash_enabled = True
+                # print("  ::  AMD flash attention enabled successfully")
                 
-            except ImportError:
-                print("  ::  Flash attention components not installed")
-            except Exception as e:
-                print(f"  ::  Flash attention setup failed: {str(e)}")
+            # except ImportError:
+                # print("  ::  Flash attention components not installed")
+            # except Exception as e:
+                # print(f"  ::  Flash attention setup failed: {str(e)}")
 
-            # Other Triton optimizations
-            if not flash_enabled:
-                print("  ::  Applying basic Triton optimizations")
-                # Add other Triton optimizations here
-                # ...
+            # # Other Triton optimizations
+            # if not flash_enabled:
+                # print("  ::  Applying basic Triton optimizations")
+                # # Add other Triton optimizations here
+                # # ...
 
         except Exception as e:
             print(f"  ::  Triton optimization failed: {str(e)}")
@@ -720,7 +721,6 @@ def do_hijack():
     torch.backends.cuda.enable_mem_efficient_sdp = do_nothing
     if hasattr(torch.backends.cuda, "enable_flash_sdp"):
         torch.backends.cuda.enable_flash_sdp(True)
-        print("  ::  Disabled CUDA flash attention")
     if hasattr(torch.backends.cuda, "enable_math_sdp"):
         torch.backends.cuda.enable_math_sdp(True)
         print("  ::  Enabled math attention fallback")