From 92d97380bd02d9883295aeb2d29365cecd9a765e Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Fri, 17 Oct 2025 15:22:59 -0700
Subject: [PATCH 1/2] Update Python 3.14 installation instructions (#10385)

Removed mention of installing pytorch nightly for Python 3.14.
---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index b0731db33..c9a0644e3 100644
--- a/README.md
+++ b/README.md
@@ -197,7 +197,7 @@ comfy install
 
 ## Manual Install (Windows, Linux)
 
-Python 3.14 will work if you comment out the `kornia` dependency in the requirements.txt file (breaks the canny node) and install pytorch nightly but it is not recommended.
+Python 3.14 will work if you comment out the `kornia` dependency in the requirements.txt file (breaks the canny node) but it is not recommended.
 
 Python 3.13 is very well supported. If you have trouble with some custom node dependencies on 3.13 you can try 3.12
 

From 9da397ea2f271080406f0c14cf4f0db7221ddf70 Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Fri, 17 Oct 2025 17:03:28 -0700
Subject: [PATCH 2/2] Disable torch compiler for cast_bias_weight function
 (#10384)

* Disable torch compiler for cast_bias_weight function

* Fix torch compile.
---
 comfy/ops.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/comfy/ops.py b/comfy/ops.py
index 56b07b44c..5feeb3571 100644
--- a/comfy/ops.py
+++ b/comfy/ops.py
@@ -25,6 +25,9 @@ import comfy.rmsnorm
 import contextlib
 
 def run_every_op():
+    if torch.compiler.is_compiling():
+        return
+
     comfy.model_management.throw_exception_if_processing_interrupted()
 
 def scaled_dot_product_attention(q, k, v, *args, **kwargs):
@@ -70,6 +73,7 @@ if torch.cuda.is_available() and torch.backends.cudnn.is_available() and Perform
 def cast_to_input(weight, input, non_blocking=False, copy=True):
     return comfy.model_management.cast_to(weight, input.dtype, input.device, non_blocking=non_blocking, copy=copy)
 
+@torch.compiler.disable()
 def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None):
     if input is not None:
         if dtype is None: