Startup Flags

Complete reference for ComfyUI main.py command-line arguments

ComfyUI accepts command-line arguments when started with python main.py. This page documents every flag defined in comfy/cli_args.py.

Windows Portable users can add flags to the .bat launch files (for example, run_nvidia_gpu.bat). See the Windows Portable guide for details.

Run python main.py --help in your ComfyUI directory for the built-in help text. Combine multiple flags as needed:

python main.py --listen 0.0.0.0 --port 8288 --disable-auto-launch --lowvram

Network & Server

Flag	Default	Description
--listen [IP]	127.0.0.1	IP address to listen on. Comma-separated list supported (e.g. 127.2.2.2,127.3.3.3). If provided without a value, defaults to 0.0.0.0,:: (all IPv4 and IPv6 interfaces).
--port	8188	Port to listen on.
--tls-keyfile PATH	—	Path to TLS (SSL) key file. Enables HTTPS. Requires --tls-certfile.
--tls-certfile PATH	—	Path to TLS (SSL) certificate file. Enables HTTPS. Requires --tls-keyfile.
--enable-cors-header [ORIGIN]	disabled	Enable CORS. Optional origin, or * for all origins when no value is given.
--max-upload-size	100	Maximum upload size in MB.
--enable-compress-response-body	disabled	Enable compressing the HTTP response body.

# Listen on all interfaces (LAN access)
python main.py --listen

# Listen on a specific IP
python main.py --listen 0.0.0.0

# Custom port with HTTPS
python main.py --port 8443 --tls-keyfile key.pem --tls-certfile cert.pem

Directories

Flag	Default	Description
--base-directory PATH	ComfyUI root	Base directory for models, custom_nodes, input, output, temp, and user directories.
--extra-model-paths-config PATH	—	Load one or more extra_model_paths.yaml files. Can be specified multiple times.
--output-directory PATH	—	Output directory. Overrides --base-directory.
--temp-directory PATH	—	Temp directory. Overrides --base-directory.
--input-directory PATH	—	Input directory. Overrides --base-directory.
--user-directory PATH	—	User directory (absolute path). Overrides --base-directory. Path must exist and be readable.

Launch & Browser

Flag	Default	Description
--auto-launch	disabled	Automatically open ComfyUI in the default browser on startup.
--disable-auto-launch	disabled	Disable auto-launching the browser.
--windows-standalone-build	disabled	Windows portable build convenience mode. Enables auto-launch on startup (equivalent to --auto-launch).

--windows-standalone-build sets auto_launch to true. --disable-auto-launch overrides it. To run as a server without opening a browser, use --disable-auto-launch.

# Run server without opening browser
python main.py --disable-auto-launch

Devices & CUDA

Flag	Default	Description
--cuda-device DEVICE_ID	—	CUDA device IDs to use, comma-separated (e.g. 0 or 0,1). Other devices are hidden.
--default-device ID	—	Default device ID. All other devices remain visible.
--cuda-malloc	auto (torch 2.0+)	Enable cudaMallocAsync. Mutually exclusive with --disable-cuda-malloc.
--disable-cuda-malloc	—	Disable cudaMallocAsync. Mutually exclusive with --cuda-malloc.
--directml [DEVICE]	—	Use torch-directml. Optional device index; defaults to -1 when no value is given.
--oneapi-device-selector STRING	—	oneAPI device selector string for Intel devices.

Precision & Inference

Flags in the Global, UNET, VAE, and Text Encoder groups below are mutually exclusive within each group. Only one flag per group can be used at a time.

Global floating point

Flag	Description
--force-fp32	Force fp32 globally. Report if this improves GPU performance.
--force-fp16	Force fp16 globally. Also sets --fp16-unet.

UNET precision

Flag	Description
--fp32-unet	Run the diffusion model in fp32.
--fp64-unet	Run the diffusion model in fp64.
--bf16-unet	Run the diffusion model in bf16.
--fp16-unet	Run the diffusion model in fp16.
--fp8_e4m3fn-unet	Store UNet weights in fp8 (e4m3fn).
--fp8_e5m2-unet	Store UNet weights in fp8 (e5m2).
--fp8_e8m0fnu-unet	Store UNet weights in fp8 (e8m0fnu).

Each FP8 flag suffix names an 8-bit float layout from the industry FP8 spec (ONNX / OCP):

• e4m3fn: 4 exponent bits, 3 mantissa bits. Good balance of precision and range for model weights on NVIDIA Ada Lovelace and newer GPUs.
• e5m2: 5 exponent bits, 2 mantissa bits. Wider dynamic range but lower precision than e4m3fn. Useful when weight magnitudes vary widely.
• e8m0fnu: 8 exponent bits, 0 mantissa bits. Maximum dynamic range with no fractional precision. Typically used as a block scaling factor (powers of two only).

VAE precision

Flag	Description
--fp16-vae	Run the VAE in fp16. May cause black images.
--fp32-vae	Run the VAE in full precision fp32.
--bf16-vae	Run the VAE in bf16.
--cpu-vae	Run the VAE on the CPU (not mutually exclusive with VAE precision flags).

Text encoder precision

Flag	Description
--fp8_e4m3fn-text-enc	Store text encoder weights in fp8 (e4m3fn).
--fp8_e5m2-text-enc	Store text encoder weights in fp8 (e5m2).
--fp16-text-enc	Store text encoder weights in fp16.
--fp32-text-enc	Store text encoder weights in fp32.
--bf16-text-enc	Store text encoder weights in bf16.

See the UNET precision section for the explanation of each FP8 format suffix.

Other inference options

Flag	Default	Description
--fp16-intermediates	disabled	Experimental: use fp16 for intermediate tensors between nodes instead of fp32.
--force-channels-last	disabled	Force channels-last memory format during inference.
--supports-fp8-compute	disabled	Act as if the device supports fp8 compute.
--enable-triton-backend	disabled	Enable Triton backend in comfy-kitchen. Disabled by default at launch.

Preview

Flag	Default	Description
--preview-method	none	Preview method for sampler nodes. Choices: none, auto, latent2rgb, taesd.
--preview-size	512	Maximum preview image size in pixels.

Cache

Cache mode flags are mutually exclusive. Only one of --cache-ram, --cache-classic, --cache-lru, or --cache-none should be used.

Flag	Default	Description
--cache-ram [GB] [GB]	enabled (default mode)	RAM pressure caching. First value: active-cache threshold in GB. Optional second value: inactive-cache/pin threshold in GB. When no values given: active = 10% of system RAM (min 2 GB, max 10 GB); inactive = 100% of system RAM (max 96 GB). Accepts at most two values.
--cache-classic	—	Use the old aggressive caching style.
--cache-lru N	0 (disabled)	LRU caching with a maximum of N node results cached. No hard upper limit; bounded by available RAM/VRAM. May use more RAM/VRAM.
--cache-none	—	Reduced RAM/VRAM usage; re-executes every node on each run.

Attention

Cross-attention method flags are mutually exclusive. Split and quad attention are ignored when xformers is used.

Flag	Description
--use-split-cross-attention	Use split cross attention optimization.
--use-quad-cross-attention	Use sub-quadratic cross attention optimization.
--use-pytorch-cross-attention	Use PyTorch 2.0 cross attention.
--use-sage-attention	Use Sage attention.
--use-flash-attention	Use FlashAttention.
--disable-xformers	Disable xformers.
--force-upcast-attention	Force attention upcasting. Report if this fixes black images. Mutually exclusive with --dont-upcast-attention.
--dont-upcast-attention	Disable all attention upcasting. For debugging only.

VRAM & Memory

VRAM mode flags (--gpu-only, --highvram, --lowvram, --novram, --cpu) are mutually exclusive.

Flag	Default	Description
--gpu-only	—	Store and run everything on the GPU (text encoders, CLIP, etc.).
--highvram	—	Keep models in GPU memory instead of unloading to CPU after use.
--lowvram	—	No effect when dynamic VRAM is enabled. Otherwise, runs text encoders on CPU.
--novram	—	Minimal VRAM usage when --lowvram is not enough.
--cpu	—	Use CPU for everything (slow).
--reserve-vram GB	OS-dependent	VRAM in GB to reserve for the OS and other software.
--async-offload [NUM_STREAMS]	enabled on Nvidia	Async weight offloading. Optional stream count (default: 2).
--disable-async-offload	—	Disable async weight offloading.
--disable-dynamic-vram	—	Disable dynamic VRAM; use estimate-based model loading.
--enable-dynamic-vram	auto on Nvidia	Enable dynamic VRAM on systems where it is not enabled by default.
--fast-disk	disabled	Prefer disk-backed dynamic loading over unpinned RAM. Useful with fast NVMe.
--force-non-blocking	disabled	Force non-blocking tensor operations. May help on non-Nvidia systems; can break some workflows.
--disable-smart-memory	disabled	Aggressively offload to RAM instead of keeping models in VRAM.
--disable-pinned-memory	disabled	Disable pinned memory use.
--mmap-torch-files	disabled	Use mmap when loading ckpt/pt files.
--disable-mmap	disabled	Do not use mmap when loading safetensors.

Performance & Debugging

Flag	Default	Description
--fast [OPT...]	disabled	Enable experimental optimizations that may affect quality or stability. --fast alone enables all. Specific options: fp16_accumulation, fp8_matrix_mult, cublas_ops, autotune.
--deterministic	disabled	Use slower deterministic PyTorch algorithms where possible. Does not guarantee identical images in all cases.
--default-hashing-function	sha256	Hash function for duplicate filename/content comparison. Choices: md5, sha1, sha256, sha512.

# Enable all fast optimizations (experimental)
python main.py --fast

# Enable specific optimizations only
python main.py --fast fp16_accumulation cublas_ops

ComfyUI Manager

See ComfyUI-Manager Installation for setup instructions.

Flag	Description
--enable-manager	Enable ComfyUI-Manager.
--disable-manager-ui	Disable Manager UI and endpoints only. Background tasks (scheduled installs, etc.) continue. Requires --enable-manager.
--enable-manager-legacy-ui	Use the legacy Manager UI. Requires --enable-manager.

Custom Nodes & API Nodes

Flag	Default	Description
--disable-all-custom-nodes	disabled	Disable loading all custom nodes.
--whitelist-custom-nodes FOLDER...	—	Custom node folders to load even when --disable-all-custom-nodes is set.
--disable-api-nodes	disabled	Disable API nodes and prevent the frontend from communicating with the internet.
--disable-metadata	disabled	Disable saving prompt metadata in output files.

# Troubleshoot custom node issues
python main.py --disable-all-custom-nodes

# Allow only specific custom nodes
python main.py --disable-all-custom-nodes --whitelist-custom-nodes ComfyUI-Manager

Frontend & API

Flag	Default	Description
--front-end-version	comfyanonymous/ComfyUI@latest	Frontend version in [owner]/[repo]@[version] format. Requires internet to download from GitHub releases. Version can be latest or a semver (e.g. 1.0.0).
--front-end-root PATH	—	Local filesystem path to the frontend directory. Overrides --front-end-version.
--comfy-api-base	https://api.comfy.org	Base URL for the ComfyUI API.
--database-url	sqlite:///<ComfyUI>/user/comfyui.db	Database URL. Use sqlite:///:memory: for in-memory.
--enable-assets	disabled	Enable the assets system (API routes, database sync, background scanning).
--feature-flag KEY[=VALUE]	—	Set a server feature flag. Bare KEY sets true. Can be repeated. Booleans and numbers are auto-converted.
--list-feature-flags	—	Print known CLI-settable feature flags as JSON and exit.

# List available feature flags
python main.py --list-feature-flags

# Set feature flags
python main.py --feature-flag show_signin_button=true

Logging & Misc

Flag	Default	Description
--verbose [LEVEL]	INFO	Logging level. Choices: DEBUG, INFO, WARNING, ERROR, CRITICAL. --verbose alone sets DEBUG.
--log-stdout	disabled	Send normal process output to stdout instead of stderr.
--dont-print-server	disabled	Do not print server output to the console.
--multi-user	disabled	Enable per-user storage.
--quick-test-for-ci	disabled	Quick startup test for CI. Exits immediately after initialization.

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This reference is based on ComfyUI comfy/cli_args.py. When upgrading ComfyUI, run python main.py --help or compare your local cli_args.py against this page to check for new or changed flags.