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# ComfyUI Global Memory Trim <div align="center">
Global native heap trimming for ComfyUI on Linux/WSL. # ComfyUI
**The most powerful and modular AI engine for content creation.**
This custom node repo installs a small global execution patch when ComfyUI loads custom nodes. The patch can call Python `gc.collect()` and glibc `malloc_trim(0)` before and/or after node execution. It is meant for workflows that repeatedly create large CPU image/video buffers through PyTorch, NumPy, OpenCV, Pillow, or native custom nodes and then stall or wedge under WSL2 memory pressure.
It also provides two optional workflow nodes: [![Website][website-shield]][website-url]
[![Dynamic JSON Badge][discord-shield]][discord-url]
[![Twitter][twitter-shield]][twitter-url]
[![Matrix][matrix-shield]][matrix-url]
<br>
[![][github-release-shield]][github-release-link]
[![][github-release-date-shield]][github-release-link]
[![][github-downloads-shield]][github-downloads-link]
[![][github-downloads-latest-shield]][github-downloads-link]
- **Global Memory Trim Now**: manually run a trim and return RSS metrics. [matrix-shield]: https://img.shields.io/badge/Matrix-000000?style=flat&logo=matrix&logoColor=white
- **Global Memory Trim Status**: return current config and last trim result. [matrix-url]: https://app.element.io/#/room/%23comfyui_space%3Amatrix.org
[website-shield]: https://img.shields.io/badge/ComfyOrg-4285F4?style=flat
[website-url]: https://www.comfy.org/
<!-- Workaround to display total user from https://github.com/badges/shields/issues/4500#issuecomment-2060079995 -->
[discord-shield]: https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2Fcomfyorg%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&logo=discord&logoColor=white&label=Discord&color=green&suffix=%20total
[discord-url]: https://discord.com/invite/comfyorg
[twitter-shield]: https://img.shields.io/twitter/follow/ComfyUI
[twitter-url]: https://x.com/ComfyUI
The global patch does **not** require adding either node to your workflow. [github-release-shield]: https://img.shields.io/github/v/release/comfyanonymous/ComfyUI?style=flat&sort=semver
[github-release-link]: https://github.com/comfyanonymous/ComfyUI/releases
[github-release-date-shield]: https://img.shields.io/github/release-date/comfyanonymous/ComfyUI?style=flat
[github-downloads-shield]: https://img.shields.io/github/downloads/comfyanonymous/ComfyUI/total?style=flat
[github-downloads-latest-shield]: https://img.shields.io/github/downloads/comfyanonymous/ComfyUI/latest/total?style=flat&label=downloads%40latest
[github-downloads-link]: https://github.com/comfyanonymous/ComfyUI/releases
## Why this exists <img width="1590" height="795" alt="ComfyUI Screenshot" src="https://github.com/user-attachments/assets/36e065e0-bfae-4456-8c7f-8369d5ea48a2" />
<br>
</div>
Some WSL2 workloads can stall when native libraries repeatedly allocate and free large CPU buffers. Python objects may be gone, but glibc arenas can retain pages. Under a WSL memory cap, that can trigger heavy reclaim or a hard-looking VM stall. `malloc_trim(0)` asks glibc to return free heap pages to the OS. ComfyUI is the AI creation engine for visual professionals who demand control over every model, every parameter, and every output. Its powerful and modular node graph interface empowers creatives to generate images, videos, 3D models, audio, and more...
- ComfyUI natively supports the latest open-source state of the art models.
- API nodes provide access to the best closed source models such as Nano Banana, Seedance, Hunyuan3D, etc.
- It is available on Windows, Linux, and macOS, locally with our [desktop application](https://www.comfy.org/download), our [portable install](#installing) or on our [cloud](https://www.comfy.org/cloud).
- The most sophisticated workflows can be exposed through a simple UI thanks to App Mode.
- It integrates seamlessly into production pipelines with our API endpoints.
This repo is intentionally CPU/native-heap focused. It does **not** directly free CUDA VRAM, unload ComfyUI models, delete ComfyUI caches, or change workflow outputs. ## Get Started
## Installation ### Local
From your ComfyUI directory: #### [Desktop Application](https://www.comfy.org/download)
- The easiest way to get started.
- Available on Windows & macOS.
#### [Windows Portable Package](#installing)
- Get the latest commits and completely portable.
- Available on Windows.
#### [Manual Install](#manual-install-windows-linux)
Supports all operating systems and GPU types (NVIDIA, AMD, Intel, Apple Silicon, Ascend).
### Cloud
#### [Comfy Cloud](https://www.comfy.org/cloud)
- Our official paid cloud version for those who can't afford local hardware.
## Examples
See what ComfyUI can do with the [newer template workflows](https://comfy.org/workflows) or old [example workflows](https://comfyanonymous.github.io/ComfyUI_examples/).
## Features
- Nodes/graph/flowchart interface to experiment and create complex Stable Diffusion workflows without needing to code anything.
- NOTE: There are many more models supported than the list below, if you want to see what is supported see our templates list inside ComfyUI.
- Image Models
- SD1.x, SD2.x ([unCLIP](https://comfyanonymous.github.io/ComfyUI_examples/unclip/))
- [SDXL](https://comfyanonymous.github.io/ComfyUI_examples/sdxl/), [SDXL Turbo](https://comfyanonymous.github.io/ComfyUI_examples/sdturbo/)
- [Stable Cascade](https://comfyanonymous.github.io/ComfyUI_examples/stable_cascade/)
- [SD3 and SD3.5](https://comfyanonymous.github.io/ComfyUI_examples/sd3/)
- Pixart Alpha and Sigma
- [AuraFlow](https://comfyanonymous.github.io/ComfyUI_examples/aura_flow/)
- [HunyuanDiT](https://comfyanonymous.github.io/ComfyUI_examples/hunyuan_dit/)
- [Flux](https://comfyanonymous.github.io/ComfyUI_examples/flux/)
- [Lumina Image 2.0](https://comfyanonymous.github.io/ComfyUI_examples/lumina2/)
- [HiDream](https://comfyanonymous.github.io/ComfyUI_examples/hidream/)
- [Qwen Image](https://comfyanonymous.github.io/ComfyUI_examples/qwen_image/)
- [Hunyuan Image 2.1](https://comfyanonymous.github.io/ComfyUI_examples/hunyuan_image/)
- [Flux 2](https://comfyanonymous.github.io/ComfyUI_examples/flux2/)
- [Z Image](https://comfyanonymous.github.io/ComfyUI_examples/z_image/)
- Ernie Image
- Image Editing Models
- [Omnigen 2](https://comfyanonymous.github.io/ComfyUI_examples/omnigen/)
- [Flux Kontext](https://comfyanonymous.github.io/ComfyUI_examples/flux/#flux-kontext-image-editing-model)
- [HiDream E1.1](https://comfyanonymous.github.io/ComfyUI_examples/hidream/#hidream-e11)
- [Qwen Image Edit](https://comfyanonymous.github.io/ComfyUI_examples/qwen_image/#edit-model)
- Video Models
- [Stable Video Diffusion](https://comfyanonymous.github.io/ComfyUI_examples/video/)
- [Mochi](https://comfyanonymous.github.io/ComfyUI_examples/mochi/)
- [LTX-Video](https://comfyanonymous.github.io/ComfyUI_examples/ltxv/)
- [Hunyuan Video](https://comfyanonymous.github.io/ComfyUI_examples/hunyuan_video/)
- [Wan 2.1](https://comfyanonymous.github.io/ComfyUI_examples/wan/)
- [Wan 2.2](https://comfyanonymous.github.io/ComfyUI_examples/wan22/)
- [Hunyuan Video 1.5](https://docs.comfy.org/tutorials/video/hunyuan/hunyuan-video-1-5)
- Audio Models
- [Stable Audio](https://comfyanonymous.github.io/ComfyUI_examples/audio/)
- [ACE Step](https://comfyanonymous.github.io/ComfyUI_examples/audio/)
- 3D Models
- [Hunyuan3D 2.0](https://docs.comfy.org/tutorials/3d/hunyuan3D-2)
- Asynchronous Queue system
- Many optimizations: Only re-executes the parts of the workflow that changes between executions.
- Smart memory management: can automatically run large models on GPUs with as low as 1GB vram with smart offloading.
- Works even if you don't have a GPU with: ```--cpu``` (slow)
- Can load ckpt and safetensors: All in one checkpoints or standalone diffusion models, VAEs and CLIP models.
- Safe loading of ckpt, pt, pth, etc.. files.
- Embeddings/Textual inversion
- [Loras (regular, locon and loha)](https://comfyanonymous.github.io/ComfyUI_examples/lora/)
- [Hypernetworks](https://comfyanonymous.github.io/ComfyUI_examples/hypernetworks/)
- Loading full workflows (with seeds) from generated PNG, WebP and FLAC files.
- Saving/Loading workflows as Json files.
- Nodes interface can be used to create complex workflows like one for [Hires fix](https://comfyanonymous.github.io/ComfyUI_examples/2_pass_txt2img/) or much more advanced ones.
- [Area Composition](https://comfyanonymous.github.io/ComfyUI_examples/area_composition/)
- [Inpainting](https://comfyanonymous.github.io/ComfyUI_examples/inpaint/) with both regular and inpainting models.
- [ControlNet and T2I-Adapter](https://comfyanonymous.github.io/ComfyUI_examples/controlnet/)
- [Upscale Models (ESRGAN, ESRGAN variants, SwinIR, Swin2SR, etc...)](https://comfyanonymous.github.io/ComfyUI_examples/upscale_models/)
- [GLIGEN](https://comfyanonymous.github.io/ComfyUI_examples/gligen/)
- [Model Merging](https://comfyanonymous.github.io/ComfyUI_examples/model_merging/)
- [LCM models and Loras](https://comfyanonymous.github.io/ComfyUI_examples/lcm/)
- Latent previews with [TAESD](#how-to-show-high-quality-previews)
- Works fully offline: core will never download anything unless you want to.
- Optional API nodes to use paid models from external providers through the online [Comfy API](https://docs.comfy.org/tutorials/api-nodes/overview) disable with: `--disable-api-nodes`
- [Config file](extra_model_paths.yaml.example) to set the search paths for models.
Workflow examples can be found on the [Examples page](https://comfyanonymous.github.io/ComfyUI_examples/)
## Release Process
ComfyUI follows a weekly release cycle targeting Monday but this regularly changes because of model releases or large changes to the codebase. There are three interconnected repositories:
1. **[ComfyUI Core](https://github.com/comfyanonymous/ComfyUI)**
- Releases a new major stable version (e.g., v0.7.0) roughly every 2 weeks.
- Starting from v0.4.0 patch versions will be used for fixes backported onto the current stable release.
- Minor versions will be used for releases off the master branch.
- Patch versions may still be used for releases on the master branch in cases where a backport would not make sense.
- Commits outside of the stable release tags may be very unstable and break many custom nodes.
- Serves as the foundation for the desktop release
2. **[Comfy Desktop](https://github.com/Comfy-Org/Comfy-Desktop)**
- Builds a new release using the latest stable core version
3. **[ComfyUI Frontend](https://github.com/Comfy-Org/ComfyUI_frontend)**
- Every 2+ weeks frontend updates are merged into the core repository
- Features are frozen for the upcoming core release
- Development continues for the next release cycle
## Shortcuts
| Keybind | Explanation |
|------------------------------------|--------------------------------------------------------------------------------------------------------------------|
| `Ctrl` + `Enter` | Queue up current graph for generation |
| `Ctrl` + `Shift` + `Enter` | Queue up current graph as first for generation |
| `Ctrl` + `Alt` + `Enter` | Cancel current generation |
| `Ctrl` + `Z`/`Ctrl` + `Y` | Undo/Redo |
| `Ctrl` + `S` | Save workflow |
| `Ctrl` + `O` | Load workflow |
| `Ctrl` + `A` | Select all nodes |
| `Alt `+ `C` | Collapse/uncollapse selected nodes |
| `Ctrl` + `M` | Mute/unmute selected nodes |
| `Ctrl` + `B` | Bypass selected nodes (acts like the node was removed from the graph and the wires reconnected through) |
| `Delete`/`Backspace` | Delete selected nodes |
| `Ctrl` + `Backspace` | Delete the current graph |
| `Space` | Move the canvas around when held and moving the cursor |
| `Ctrl`/`Shift` + `Click` | Add clicked node to selection |
| `Ctrl` + `C`/`Ctrl` + `V` | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes) |
| `Ctrl` + `C`/`Ctrl` + `Shift` + `V` | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
| `Shift` + `Drag` | Move multiple selected nodes at the same time |
| `Ctrl` + `D` | Load default graph |
| `Alt` + `+` | Canvas Zoom in |
| `Alt` + `-` | Canvas Zoom out |
| `Ctrl` + `Shift` + LMB + Vertical drag | Canvas Zoom in/out |
| `P` | Pin/Unpin selected nodes |
| `Ctrl` + `G` | Group selected nodes |
| `Q` | Toggle visibility of the queue |
| `H` | Toggle visibility of history |
| `R` | Refresh graph |
| `F` | Show/Hide menu |
| `.` | Fit view to selection (Whole graph when nothing is selected) |
| Double-Click LMB | Open node quick search palette |
| `Shift` + Drag | Move multiple wires at once |
| `Ctrl` + `Alt` + LMB | Disconnect all wires from clicked slot |
`Ctrl` can also be replaced with `Cmd` instead for macOS users
# Installing
## Windows Portable
There is a portable standalone build for Windows that should work for running on Nvidia GPUs or for running on your CPU only on the [releases page](https://github.com/comfyanonymous/ComfyUI/releases).
### [Direct link to download](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia.7z)
Simply download, extract with [7-Zip](https://7-zip.org) or with the windows explorer on recent windows versions and run. For smaller models you normally only need to put the checkpoints (the huge ckpt/safetensors files) in: ComfyUI\models\checkpoints but many of the larger models have multiple files. Make sure to follow the instructions to know which subfolder to put them in ComfyUI\models\
If you have trouble extracting it, right click the file -> properties -> unblock
The portable above currently comes with python 3.13 and pytorch cuda 13.0. Update your Nvidia drivers if it doesn't start.
#### All Official Portable Downloads:
[Portable for AMD GPUs](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_amd.7z)
[Portable for Intel GPUs](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_intel.7z)
[Portable for Nvidia GPUs](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia.7z) (supports 20 series and above).
[Portable for Nvidia GPUs with pytorch cuda 12.6 and python 3.12](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia_cu126.7z) (Supports Nvidia 10 series and older GPUs).
#### How do I share models between another UI and ComfyUI?
See the [Config file](extra_model_paths.yaml.example) to set the search paths for models. In the standalone windows build you can find this file in the ComfyUI directory. Rename this file to extra_model_paths.yaml and edit it with your favorite text editor.
## [comfy-cli](https://docs.comfy.org/comfy-cli/getting-started)
You can install and start ComfyUI using comfy-cli:
```bash ```bash
git clone https://github.com/xmarre/ComfyUI-Global-Memory-Trim custom_nodes/ComfyUI-Global-Memory-Trim pip install comfy-cli
comfy install
``` ```
Or copy this folder into: ## Manual Install (Windows, Linux)
```text Python 3.14 works but some custom nodes may have issues. The free threaded variant works but some dependencies will enable the GIL so it's not fully supported.
ComfyUI/custom_nodes/ComfyUI-Global-Memory-Trim
```
Restart ComfyUI. On startup you should see a log line similar to: Python 3.13 is very well supported. If you have trouble with some custom node dependencies on 3.13 you can try 3.12
```text torch 2.4 and above is supported but some features and optimizations might only work on newer versions. We generally recommend using the latest major version of pytorch with the latest cuda version unless it is less than 2 weeks old.
Installed global memory trim patch: enabled=True before=False after=True ...
```
## Performance-oriented WSL setup ### Instructions:
This is the current practical setup I use for a large WSL2 ComfyUI workflow with heavy model switching, Flux/SDXL/SeedVR2/detailer passes, and large CPU image buffers. Git clone this repo.
The important parts are: Put your SD checkpoints (the huge ckpt/safetensors files) in: models/checkpoints
- Keep ComfyUI on `--highvram` for performance. Put your VAE in: models/vae
- Disable async weight offload and pinned memory on WSL.
- Do **not** force `--disable-cuda-malloc` here; the normal CUDA allocator path avoids the VRAM over-reservation/overflow seen with the native allocator path in this workflow.
- Keep `PYTORCH_CUDA_ALLOC_CONF` unset.
- Use glibc trim thresholds and the global trim hook to reduce CPU/native heap retention.
- Keep SeedVR2 BF16 forced on if using the patched SeedVR2 import probe workaround and wanting the higher-quality 7B path.
```bash
#!/usr/bin/env bash
set -e
_hold_terminal_on_failure() { ### AMD GPUs (Linux)
local rc=$?
if [ "$rc" -ne 0 ]; then
printf '\nComfyUI launcher exited with status %d\n' "$rc" >&2
printf 'Dropping into interactive shell so the terminal stays open.\n' >&2
exec bash -i
fi
}
trap _hold_terminal_on_failure EXIT
source ~/miniconda3/etc/profile.d/conda.sh AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
conda activate comfy312
# Native/CPU heap behavior. These do not free CUDA VRAM directly. ```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2```
export MALLOC_MMAP_THRESHOLD_=65536
export MALLOC_TRIM_THRESHOLD_=65536
# Global trim hook. This is the command to install the nightly with ROCm 7.2 which might have some performance improvements:
# BEFORE=1 is more aggressive and can help before large model/node transitions.
# LOG=1 is useful while validating. Set it to 0 once stable.
export COMFYUI_GLOBAL_TRIM=1
export COMFYUI_GLOBAL_TRIM_AFTER=1
export COMFYUI_GLOBAL_TRIM_BEFORE=1
export COMFYUI_GLOBAL_TRIM_GC=1
export COMFYUI_GLOBAL_TRIM_INTERVAL=1
export COMFYUI_GLOBAL_TRIM_LOG=1
export COMFYUI_GLOBAL_TRIM_MIN_RSS_MB=8192
# Optional, workflow-specific: keep SeedVR2 on BF16 without running an import-time CUDA probe. ```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2```
export SEEDVR2_FORCE_BFLOAT16=1
unset SEEDVR2_IMPORT_BFLOAT16_PROBE
# Do not force PyTorch's allocator through the environment.
unset PYTORCH_CUDA_ALLOC_CONF
# Optional, workflow-specific memory reduction for SuperBeasts. ### AMD GPUs (Experimental: Windows and Linux), RDNA 3, 3.5 and 4 only.
export SUPERBEASTS_SPCA_RETURN_RESIDUALS=false
export SUPERBEASTS_HDR_MALLOC_TRIM=true
export PYTHONFAULTHANDLER=1 These have less hardware support than the builds above but they work on windows. You also need to install the pytorch version specific to your hardware.
cd ~/ComfyUI RDNA 3 (RX 7000 series):
set +e ```pip install --pre torch torchvision torchaudio --index-url https://rocm.nightlies.amd.com/v2/gfx110X-all/```
python main.py \
--listen 0.0.0.0 \
--port 8188 \
--fast fp16_accumulation \
--highvram \
--use-pytorch-cross-attention \
--disable-async-offload \
--disable-pinned-memory \
"$@"
status=$?
set -e
exit "$status" RDNA 3.5 (Strix halo/Ryzen AI Max+ 365):
```
### After validating stability ```pip install --pre torch torchvision torchaudio --index-url https://rocm.nightlies.amd.com/v2/gfx1151/```
Once the workflow is stable, reduce log overhead first: RDNA 4 (RX 9000 series):
```bash ```pip install --pre torch torchvision torchaudio --index-url https://rocm.nightlies.amd.com/v2/gfx120X-all/```
export COMFYUI_GLOBAL_TRIM_LOG=0
```
Then, if performance still needs tuning, test one change at a time: ### Intel GPUs (Windows and Linux)
```bash Intel Arc GPU users can install native PyTorch with torch.xpu support using pip. More information can be found [here](https://pytorch.org/docs/main/notes/get_start_xpu.html)
export COMFYUI_GLOBAL_TRIM_BEFORE=0
```
or: 1. To install PyTorch xpu, use the following command:
```bash ```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/xpu```
export COMFYUI_GLOBAL_TRIM_INTERVAL=2
```
If wedges return, restore the previous value. This is the command to install the Pytorch xpu nightly which might have some performance improvements:
## Conservative diagnostic WSL setup ```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/xpu```
For reproducing or isolating CPU/native heap stalls, use the more conservative version below. It clamps native CPU thread pools and limits glibc arenas, which can improve WSL stability but may slow CPU-heavy nodes. ### NVIDIA
```bash Nvidia users should install stable pytorch using this command:
export OMP_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export MKL_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OPENCV_OPENCL_RUNTIME=disabled
export MALLOC_ARENA_MAX=1 ```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130```
export MALLOC_MMAP_THRESHOLD_=65536
export MALLOC_TRIM_THRESHOLD_=65536
export COMFYUI_GLOBAL_TRIM=1 This is the command to install pytorch nightly instead which might have performance improvements.
export COMFYUI_GLOBAL_TRIM_AFTER=1
export COMFYUI_GLOBAL_TRIM_BEFORE=0
export COMFYUI_GLOBAL_TRIM_GC=1
export COMFYUI_GLOBAL_TRIM_INTERVAL=1
export COMFYUI_GLOBAL_TRIM_LOG=0
export COMFYUI_GLOBAL_TRIM_MIN_RSS_MB=8192
```
Use this when the problem is clearly CPU/native memory pressure rather than VRAM pressure. ```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132```
## Configuration #### Troubleshooting
All configuration is via environment variables. If you get the "Torch not compiled with CUDA enabled" error, uninstall torch with:
| Variable | Default | Meaning | ```pip uninstall torch```
|---|---:|---|
| `COMFYUI_GLOBAL_TRIM` | `1` | Enable/disable the global patch. |
| `COMFYUI_GLOBAL_TRIM_AFTER` | `1` | Trim after node execution. |
| `COMFYUI_GLOBAL_TRIM_BEFORE` | `0` | Also trim before node execution. More aggressive, useful for testing or fragile WSL setups. |
| `COMFYUI_GLOBAL_TRIM_GC` | `1` | Run `gc.collect()` before `malloc_trim(0)`. |
| `COMFYUI_GLOBAL_TRIM_INTERVAL` | `1` | Trim every N trim opportunities. Use `2`, `4`, etc. to reduce overhead. |
| `COMFYUI_GLOBAL_TRIM_MIN_RSS_MB` | `0` | Only trim when process RSS is at least this value. `0` means always. |
| `COMFYUI_GLOBAL_TRIM_LOG` | `0` | Log every trim with RSS before/after. Very noisy; enable only while diagnosing. |
| `COMFYUI_GLOBAL_TRIM_WARN_NO_LIBC` | `1` | Warn when glibc `malloc_trim` cannot be loaded. |
## Notes And install it again with the command above.
- Linux/WSL only. On non-Linux platforms the patch becomes a no-op. ### Dependencies
- `malloc_trim(0)` only returns already-free native heap pages. It does not free live tensors, ComfyUI outputs, model weights, or Python objects that are still referenced.
- This is **not** a VRAM fixer. It targets CPU/native heap retention.
- `--disable-cuda-malloc` can change CUDA allocator behavior and may increase VRAM reservation/fragmentation in some workflows. Do not assume it is safer unless you specifically need it.
- `--disable-async-offload` and `--disable-pinned-memory` can be useful on WSL when async offload/pinned-memory paths cause wedges.
- `COMFYUI_GLOBAL_TRIM_LOG=1` is diagnostic only. Turn it off for normal use.
## License Install the dependencies by opening your terminal inside the ComfyUI folder and:
MIT ```pip install -r requirements.txt```
After this you should have everything installed and can proceed to running ComfyUI.
### Others:
#### Apple Mac silicon
You can install ComfyUI in Apple Mac silicon (M1, M2, M3 or M4) with any recent macOS version.
1. Install pytorch nightly. For instructions, read the [Accelerated PyTorch training on Mac](https://developer.apple.com/metal/pytorch/) Apple Developer guide (make sure to install the latest pytorch nightly).
1. Follow the [ComfyUI manual installation](#manual-install-windows-linux) instructions for Windows and Linux.
1. Install the ComfyUI [dependencies](#dependencies). If you have another Stable Diffusion UI [you might be able to reuse the dependencies](#i-already-have-another-ui-for-stable-diffusion-installed-do-i-really-have-to-install-all-of-these-dependencies).
1. Launch ComfyUI by running `python main.py`
> **Note**: Remember to add your models, VAE, LoRAs etc. to the corresponding Comfy folders, as discussed in [ComfyUI manual installation](#manual-install-windows-linux).
#### Ascend NPUs
For models compatible with Ascend Extension for PyTorch (torch_npu). To get started, ensure your environment meets the prerequisites outlined on the [installation](https://ascend.github.io/docs/sources/ascend/quick_install.html) page. Here's a step-by-step guide tailored to your platform and installation method:
1. Begin by installing the recommended or newer kernel version for Linux as specified in the Installation page of torch-npu, if necessary.
2. Proceed with the installation of Ascend Basekit, which includes the driver, firmware, and CANN, following the instructions provided for your specific platform.
3. Next, install the necessary packages for torch-npu by adhering to the platform-specific instructions on the [Installation](https://ascend.github.io/docs/sources/pytorch/install.html#pytorch) page.
4. Finally, adhere to the [ComfyUI manual installation](#manual-install-windows-linux) guide for Linux. Once all components are installed, you can run ComfyUI as described earlier.
#### Cambricon MLUs
For models compatible with Cambricon Extension for PyTorch (torch_mlu). Here's a step-by-step guide tailored to your platform and installation method:
1. Install the Cambricon CNToolkit by adhering to the platform-specific instructions on the [Installation](https://www.cambricon.com/docs/sdk_1.15.0/cntoolkit_3.7.2/cntoolkit_install_3.7.2/index.html)
2. Next, install the PyTorch(torch_mlu) following the instructions on the [Installation](https://www.cambricon.com/docs/sdk_1.15.0/cambricon_pytorch_1.17.0/user_guide_1.9/index.html)
3. Launch ComfyUI by running `python main.py`
#### Iluvatar Corex
For models compatible with Iluvatar Extension for PyTorch. Here's a step-by-step guide tailored to your platform and installation method:
1. Install the Iluvatar Corex Toolkit by adhering to the platform-specific instructions on the [Installation](https://support.iluvatar.com/#/DocumentCentre?id=1&nameCenter=2&productId=520117912052801536)
2. Launch ComfyUI by running `python main.py`
## [ComfyUI-Manager](https://github.com/Comfy-Org/ComfyUI-Manager/tree/manager-v4)
**ComfyUI-Manager** is an extension that allows you to easily install, update, and manage custom nodes for ComfyUI.
### Setup
1. Install the manager dependencies:
```bash
pip install -r manager_requirements.txt
```
2. Enable the manager with the `--enable-manager` flag when running ComfyUI:
```bash
python main.py --enable-manager
```
### Command Line Options
| Flag | Description |
|------|-------------|
| `--enable-manager` | Enable ComfyUI-Manager |
| `--enable-manager-legacy-ui` | Use the legacy manager UI instead of the new UI (implies `--enable-manager`) |
| `--disable-manager-ui` | Disable the manager UI and endpoints while keeping background features like security checks and scheduled installation completion (requires `--enable-manager`) |
# Running
```python main.py```
### For AMD cards not officially supported by ROCm
Try running it with this command if you have issues:
For 6700, 6600 and maybe other RDNA2 or older: ```HSA_OVERRIDE_GFX_VERSION=10.3.0 python main.py```
For AMD 7600 and maybe other RDNA3 cards: ```HSA_OVERRIDE_GFX_VERSION=11.0.0 python main.py```
### AMD ROCm Tips
You can try setting this env variable `PYTORCH_TUNABLEOP_ENABLED=1` which might speed things up at the cost of a very slow initial run.
# Notes
Only parts of the graph that have an output with all the correct inputs will be executed.
Only parts of the graph that change from each execution to the next will be executed, if you submit the same graph twice only the first will be executed. If you change the last part of the graph only the part you changed and the part that depends on it will be executed.
Dragging a generated png on the webpage or loading one will give you the full workflow including seeds that were used to create it.
You can use () to change emphasis of a word or phrase like: (good code:1.2) or (bad code:0.8). The default emphasis for () is 1.1. To use () characters in your actual prompt escape them like \\( or \\).
You can use {day|night}, for wildcard/dynamic prompts. With this syntax "{wild|card|test}" will be randomly replaced by either "wild", "card" or "test" by the frontend every time you queue the prompt. To use {} characters in your actual prompt escape them like: \\{ or \\}.
Dynamic prompts also support C-style comments, like `// comment` or `/* comment */`.
To use a textual inversion concepts/embeddings in a text prompt put them in the models/embeddings directory and use them in the CLIPTextEncode node like this (you can omit the .pt extension):
```embedding:embedding_filename.pt```
## How to show high-quality previews?
Use ```--preview-method auto``` to enable previews.
The default installation includes a fast latent preview method that's low-resolution. To enable higher-quality previews with [TAESD](https://github.com/madebyollin/taesd), download the [taesd_decoder.pth, taesdxl_decoder.pth, taesd3_decoder.pth and taef1_decoder.pth](https://github.com/madebyollin/taesd/) and place them in the `models/vae_approx` folder. Once they're installed, restart ComfyUI and launch it with `--preview-method taesd` to enable high-quality previews.
## How to use TLS/SSL?
Generate a self-signed certificate (not appropriate for shared/production use) and key by running the command: `openssl req -x509 -newkey rsa:4096 -keyout key.pem -out cert.pem -sha256 -days 3650 -nodes -subj "/C=XX/ST=StateName/L=CityName/O=CompanyName/OU=CompanySectionName/CN=CommonNameOrHostname"`
Use `--tls-keyfile key.pem --tls-certfile cert.pem` to enable TLS/SSL, the app will now be accessible with `https://...` instead of `http://...`.
> Note: Windows users can use [alexisrolland/docker-openssl](https://github.com/alexisrolland/docker-openssl) or one of the [3rd party binary distributions](https://wiki.openssl.org/index.php/Binaries) to run the command example above.
<br/><br/>If you use a container, note that the volume mount `-v` can be a relative path so `... -v ".\:/openssl-certs" ...` would create the key & cert files in the current directory of your command prompt or powershell terminal.
## Support and dev channel
[Discord](https://comfy.org/discord): Try the #help or #feedback channels.
[Matrix space: #comfyui_space:matrix.org](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) (it's like discord but open source).
See also: [https://www.comfy.org/](https://www.comfy.org/)
> _psst — we're hiring!_ Help build ComfyUI: [comfy.org/careers](https://www.comfy.org/careers)
## Frontend Development
As of August 15, 2024, we have transitioned to a new frontend, which is now hosted in a separate repository: [ComfyUI Frontend](https://github.com/Comfy-Org/ComfyUI_frontend). The compiled JS files (from TS/Vue) are published to [pypi](https://pypi.org/project/comfyui-frontend-package) and installed as a dependency in ComfyUI.
### Reporting Issues and Requesting Features
For any bugs, issues, or feature requests related to the frontend, please use the [ComfyUI Frontend repository](https://github.com/Comfy-Org/ComfyUI_frontend). This will help us manage and address frontend-specific concerns more efficiently.
### Using the Latest Frontend
The new frontend is now the default for ComfyUI. However, please note:
1. The frontend in the main ComfyUI repository is updated fortnightly.
2. Daily releases are available in the separate frontend repository.
To use the most up-to-date frontend version:
1. For the latest daily release, launch ComfyUI with this command line argument:
```
--front-end-version Comfy-Org/ComfyUI_frontend@latest
```
2. For a specific version, replace `latest` with the desired version number:
```
--front-end-version Comfy-Org/ComfyUI_frontend@1.2.2
```
This approach allows you to easily switch between the stable fortnightly release and the cutting-edge daily updates, or even specific versions for testing purposes.
# QA
### Which GPU should I buy for this?
[See this page for some recommendations](https://github.com/comfyanonymous/ComfyUI/wiki/Which-GPU-should-I-buy-for-ComfyUI)