From 7ce3f64c784430e15731d344affffb48c55a0eaa Mon Sep 17 00:00:00 2001
From: "Daxiong (Lin)" <contact@comfyui-wiki.com>
Date: Wed, 15 Apr 2026 08:35:27 +0800
Subject: [PATCH 1/4] Update workflow templates to v0.9.54 (#13412)

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 7f065e0d4..e45a20aaf 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.42.11
-comfyui-workflow-templates==0.9.50
+comfyui-workflow-templates==0.9.54
 comfyui-embedded-docs==0.4.3
 torch
 torchsde

From cb0bbde402cfb72559cc8b00f679d7735dff5c40 Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Tue, 14 Apr 2026 19:54:47 -0700
Subject: [PATCH 2/4] Fix ernie on devices that don't support fp64. (#13414)

---
 comfy/ldm/ernie/model.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/comfy/ldm/ernie/model.py b/comfy/ldm/ernie/model.py
index 3dbab8dc0..f7cdb51e6 100644
--- a/comfy/ldm/ernie/model.py
+++ b/comfy/ldm/ernie/model.py
@@ -15,7 +15,7 @@ def rope(pos: torch.Tensor, dim: int, theta: int) -> torch.Tensor:
 
     scale = torch.arange(0, dim, 2, dtype=torch.float64, device=device) / dim
     omega = 1.0 / (theta**scale)
-    out = torch.einsum("...n,d->...nd", pos, omega)
+    out = torch.einsum("...n,d->...nd", pos.to(device), omega)
     out = torch.stack([torch.cos(out), torch.sin(out)], dim=0)
     return out.to(dtype=torch.float32, device=pos.device)
 

From 8f374716ee98d378d403ebc61250e091ecd3a25c Mon Sep 17 00:00:00 2001
From: comfyanonymous <comfyanonymous@protonmail.com>
Date: Tue, 14 Apr 2026 22:56:13 -0400
Subject: [PATCH 3/4] ComfyUI v0.19.1

---
 comfyui_version.py | 2 +-
 pyproject.toml     | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/comfyui_version.py b/comfyui_version.py
index 0da11d5fa..3c6dac3d9 100644
--- a/comfyui_version.py
+++ b/comfyui_version.py
@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.19.0"
+__version__ = "0.19.1"
diff --git a/pyproject.toml b/pyproject.toml
index e8d4a9742..006ed9985 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.19.0"
+version = "0.19.1"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"

From 1de83f91c34a3396c667d764224054ba87027e82 Mon Sep 17 00:00:00 2001
From: Jun Yamog <jkyamog@gmail.com>
Date: Wed, 15 Apr 2026 21:10:36 +1200
Subject: [PATCH 4/4] Fix OOM regression in _apply() for quantized models
 during inference (#13372)

Skip unnecessary clone of inference-mode tensors when already inside
torch.inference_mode(), matching the existing guard in set_attr_param.
The unconditional clone introduced in 20561aa9 caused transient VRAM
doubling during model movement for FP8/quantized models.
---
 comfy/ops.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/comfy/ops.py b/comfy/ops.py
index b5cd1d47e..7a9b4b84c 100644
--- a/comfy/ops.py
+++ b/comfy/ops.py
@@ -1151,7 +1151,7 @@ def mixed_precision_ops(quant_config={}, compute_dtype=torch.bfloat16, full_prec
                     if param is None:
                         continue
                     p = fn(param)
-                    if p.is_inference():
+                    if (not torch.is_inference_mode_enabled()) and p.is_inference():
                         p = p.clone()
                     self.register_parameter(key, torch.nn.Parameter(p, requires_grad=False))
                 for key, buf in self._buffers.items():