Instructions to use vidfom/Ltx-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use vidfom/Ltx-3 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="vidfom/Ltx-3", filename="ComfyUI/models/text_encoders/gemma-3-12b-it-qat-UD-Q4_K_XL.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use vidfom/Ltx-3 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use Docker
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use vidfom/Ltx-3 with Ollama:
ollama run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Unsloth Studio new
How to use vidfom/Ltx-3 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for vidfom/Ltx-3 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for vidfom/Ltx-3 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vidfom/Ltx-3 to start chatting
- Docker Model Runner
How to use vidfom/Ltx-3 with Docker Model Runner:
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Lemonade
How to use vidfom/Ltx-3 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vidfom/Ltx-3:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Ltx-3-UD-Q4_K_XL
List all available models
lemonade list
File size: 21,688 Bytes
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comfy.options.enable_args_parsing()
import os
import importlib.util
import shutil
import importlib.metadata
import folder_paths
import time
from comfy.cli_args import args, enables_dynamic_vram
from app.logger import setup_logger
from app.assets.seeder import asset_seeder
from app.assets.services import register_output_files
import itertools
import utils.extra_config
from utils.mime_types import init_mime_types
import faulthandler
import logging
import sys
from comfy_execution.progress import get_progress_state
from comfy_execution.utils import get_executing_context
from comfy_api import feature_flags
from app.database.db import init_db, dependencies_available
if __name__ == "__main__":
#NOTE: These do not do anything on core ComfyUI, they are for custom nodes.
os.environ['HF_HUB_DISABLE_TELEMETRY'] = '1'
os.environ['DO_NOT_TRACK'] = '1'
setup_logger(log_level=args.verbose, use_stdout=args.log_stdout)
faulthandler.enable(file=sys.stderr, all_threads=False)
import comfy_aimdo.control
if enables_dynamic_vram():
comfy_aimdo.control.init()
if os.name == "nt":
os.environ['MIMALLOC_PURGE_DELAY'] = '0'
if __name__ == "__main__":
os.environ['TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL'] = '1'
if args.default_device is not None:
default_dev = args.default_device
devices = list(range(32))
devices.remove(default_dev)
devices.insert(0, default_dev)
devices = ','.join(map(str, devices))
os.environ['CUDA_VISIBLE_DEVICES'] = str(devices)
os.environ['HIP_VISIBLE_DEVICES'] = str(devices)
if args.cuda_device is not None:
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
os.environ['HIP_VISIBLE_DEVICES'] = str(args.cuda_device)
os.environ["ASCEND_RT_VISIBLE_DEVICES"] = str(args.cuda_device)
logging.info("Set cuda device to: {}".format(args.cuda_device))
if args.oneapi_device_selector is not None:
os.environ['ONEAPI_DEVICE_SELECTOR'] = args.oneapi_device_selector
logging.info("Set oneapi device selector to: {}".format(args.oneapi_device_selector))
if args.deterministic:
if 'CUBLAS_WORKSPACE_CONFIG' not in os.environ:
os.environ['CUBLAS_WORKSPACE_CONFIG'] = ":4096:8"
import cuda_malloc
if "rocm" in cuda_malloc.get_torch_version_noimport():
os.environ['OCL_SET_SVM_SIZE'] = '262144' # set at the request of AMD
def handle_comfyui_manager_unavailable():
manager_req_path = os.path.join(os.path.dirname(os.path.abspath(folder_paths.__file__)), "manager_requirements.txt")
uv_available = shutil.which("uv") is not None
pip_cmd = f"{sys.executable} -m pip install -r {manager_req_path}"
msg = f"\n\nTo use the `--enable-manager` feature, the `comfyui-manager` package must be installed first.\ncommand:\n\t{pip_cmd}"
if uv_available:
msg += f"\nor using uv:\n\tuv pip install -r {manager_req_path}"
msg += "\n"
logging.warning(msg)
args.enable_manager = False
if args.enable_manager:
if importlib.util.find_spec("comfyui_manager"):
import comfyui_manager
if not comfyui_manager.__file__ or not comfyui_manager.__file__.endswith('__init__.py'):
handle_comfyui_manager_unavailable()
else:
handle_comfyui_manager_unavailable()
def apply_custom_paths():
# extra model paths
extra_model_paths_config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "extra_model_paths.yaml")
if os.path.isfile(extra_model_paths_config_path):
utils.extra_config.load_extra_path_config(extra_model_paths_config_path)
if args.extra_model_paths_config:
for config_path in itertools.chain(*args.extra_model_paths_config):
utils.extra_config.load_extra_path_config(config_path)
# --output-directory, --input-directory, --user-directory
if args.output_directory:
output_dir = os.path.abspath(args.output_directory)
logging.info(f"Setting output directory to: {output_dir}")
folder_paths.set_output_directory(output_dir)
# These are the default folders that checkpoints, clip and vae models will be saved to when using CheckpointSave, etc.. nodes
folder_paths.add_model_folder_path("checkpoints", os.path.join(folder_paths.get_output_directory(), "checkpoints"))
folder_paths.add_model_folder_path("clip", os.path.join(folder_paths.get_output_directory(), "clip"))
folder_paths.add_model_folder_path("vae", os.path.join(folder_paths.get_output_directory(), "vae"))
folder_paths.add_model_folder_path("diffusion_models",
os.path.join(folder_paths.get_output_directory(), "diffusion_models"))
folder_paths.add_model_folder_path("loras", os.path.join(folder_paths.get_output_directory(), "loras"))
if args.input_directory:
input_dir = os.path.abspath(args.input_directory)
logging.info(f"Setting input directory to: {input_dir}")
folder_paths.set_input_directory(input_dir)
if args.user_directory:
user_dir = os.path.abspath(args.user_directory)
logging.info(f"Setting user directory to: {user_dir}")
folder_paths.set_user_directory(user_dir)
def execute_prestartup_script():
if args.disable_all_custom_nodes and len(args.whitelist_custom_nodes) == 0:
return
def execute_script(script_path):
module_name = os.path.splitext(script_path)[0]
try:
spec = importlib.util.spec_from_file_location(module_name, script_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return True
except Exception as e:
logging.error(f"Failed to execute startup-script: {script_path} / {e}")
return False
node_paths = folder_paths.get_folder_paths("custom_nodes")
for custom_node_path in node_paths:
possible_modules = os.listdir(custom_node_path)
node_prestartup_times = []
for possible_module in possible_modules:
module_path = os.path.join(custom_node_path, possible_module)
if args.enable_manager:
if comfyui_manager.should_be_disabled(module_path):
continue
if os.path.isfile(module_path) or module_path.endswith(".disabled") or module_path == "__pycache__":
continue
script_path = os.path.join(module_path, "prestartup_script.py")
if os.path.exists(script_path):
if args.disable_all_custom_nodes and possible_module not in args.whitelist_custom_nodes:
logging.info(f"Prestartup Skipping {possible_module} due to disable_all_custom_nodes and whitelist_custom_nodes")
continue
time_before = time.perf_counter()
success = execute_script(script_path)
node_prestartup_times.append((time.perf_counter() - time_before, module_path, success))
if len(node_prestartup_times) > 0:
logging.info("\nPrestartup times for custom nodes:")
for n in sorted(node_prestartup_times):
if n[2]:
import_message = ""
else:
import_message = " (PRESTARTUP FAILED)"
logging.info("{:6.1f} seconds{}: {}".format(n[0], import_message, n[1]))
logging.info("")
apply_custom_paths()
init_mime_types()
if args.enable_manager:
comfyui_manager.prestartup()
execute_prestartup_script()
# Main code
import asyncio
import threading
import gc
if 'torch' in sys.modules:
logging.warning("WARNING: Potential Error in code: Torch already imported, torch should never be imported before this point.")
import comfy.utils
import execution
import server
from protocol import BinaryEventTypes
import nodes
import comfy.model_management
import comfyui_version
import app.logger
import hook_breaker_ac10a0
import comfy.memory_management
import comfy.model_patcher
if args.enable_dynamic_vram or (enables_dynamic_vram() and comfy.model_management.is_nvidia() and not comfy.model_management.is_wsl()):
if (not args.enable_dynamic_vram) and (comfy.model_management.torch_version_numeric < (2, 8)):
logging.warning("Unsupported Pytorch detected. DynamicVRAM support requires Pytorch version 2.8 or later. Falling back to legacy ModelPatcher. VRAM estimates may be unreliable especially on Windows")
elif comfy_aimdo.control.init_device(comfy.model_management.get_torch_device().index):
if args.verbose == 'DEBUG':
comfy_aimdo.control.set_log_debug()
elif args.verbose == 'CRITICAL':
comfy_aimdo.control.set_log_critical()
elif args.verbose == 'ERROR':
comfy_aimdo.control.set_log_error()
elif args.verbose == 'WARNING':
comfy_aimdo.control.set_log_warning()
else: #INFO
comfy_aimdo.control.set_log_info()
comfy.model_patcher.CoreModelPatcher = comfy.model_patcher.ModelPatcherDynamic
comfy.memory_management.aimdo_enabled = True
logging.info("DynamicVRAM support detected and enabled")
else:
logging.warning("No working comfy-aimdo install detected. DynamicVRAM support disabled. Falling back to legacy ModelPatcher. VRAM estimates may be unreliable especially on Windows")
def cuda_malloc_warning():
device = comfy.model_management.get_torch_device()
device_name = comfy.model_management.get_torch_device_name(device)
cuda_malloc_warning = False
if "cudaMallocAsync" in device_name:
for b in cuda_malloc.blacklist:
if b in device_name:
cuda_malloc_warning = True
if cuda_malloc_warning:
logging.warning("\nWARNING: this card most likely does not support cuda-malloc, if you get \"CUDA error\" please run ComfyUI with: --disable-cuda-malloc\n")
def _collect_output_absolute_paths(history_result: dict) -> list[str]:
"""Extract absolute file paths for output items from a history result."""
paths: list[str] = []
seen: set[str] = set()
for node_output in history_result.get("outputs", {}).values():
for items in node_output.values():
if not isinstance(items, list):
continue
for item in items:
if not isinstance(item, dict):
continue
item_type = item.get("type")
if item_type not in ("output", "temp"):
continue
base_dir = folder_paths.get_directory_by_type(item_type)
if base_dir is None:
continue
base_dir = os.path.abspath(base_dir)
filename = item.get("filename")
if not filename:
continue
abs_path = os.path.abspath(
os.path.join(base_dir, item.get("subfolder", ""), filename)
)
if not abs_path.startswith(base_dir + os.sep) and abs_path != base_dir:
continue
if abs_path not in seen:
seen.add(abs_path)
paths.append(abs_path)
return paths
def prompt_worker(q, server_instance):
current_time: float = 0.0
cache_ram = args.cache_ram
if cache_ram < 0:
cache_ram = min(32.0, max(4.0, comfy.model_management.total_ram * 0.25 / 1024.0))
cache_type = execution.CacheType.CLASSIC
if args.cache_lru > 0:
cache_type = execution.CacheType.LRU
elif cache_ram > 0:
cache_type = execution.CacheType.RAM_PRESSURE
elif args.cache_none:
cache_type = execution.CacheType.NONE
e = execution.PromptExecutor(server_instance, cache_type=cache_type, cache_args={ "lru" : args.cache_lru, "ram" : cache_ram } )
last_gc_collect = 0
need_gc = False
gc_collect_interval = 10.0
while True:
timeout = 1000.0
if need_gc:
timeout = max(gc_collect_interval - (current_time - last_gc_collect), 0.0)
queue_item = q.get(timeout=timeout)
if queue_item is not None:
item, item_id = queue_item
execution_start_time = time.perf_counter()
prompt_id = item[1]
server_instance.last_prompt_id = prompt_id
sensitive = item[5]
extra_data = item[3].copy()
for k in sensitive:
extra_data[k] = sensitive[k]
asset_seeder.pause()
e.execute(item[2], prompt_id, extra_data, item[4])
need_gc = True
remove_sensitive = lambda prompt: prompt[:5] + prompt[6:]
q.task_done(item_id,
e.history_result,
status=execution.PromptQueue.ExecutionStatus(
status_str='success' if e.success else 'error',
completed=e.success,
messages=e.status_messages), process_item=remove_sensitive)
if server_instance.client_id is not None:
server_instance.send_sync("executing", {"node": None, "prompt_id": prompt_id}, server_instance.client_id)
current_time = time.perf_counter()
execution_time = current_time - execution_start_time
# Log Time in a more readable way after 10 minutes
if execution_time > 600:
execution_time = time.strftime("%H:%M:%S", time.gmtime(execution_time))
logging.info(f"Prompt executed in {execution_time}")
else:
logging.info("Prompt executed in {:.2f} seconds".format(execution_time))
if not asset_seeder.is_disabled():
paths = _collect_output_absolute_paths(e.history_result)
register_output_files(paths, job_id=prompt_id)
flags = q.get_flags()
free_memory = flags.get("free_memory", False)
if flags.get("unload_models", free_memory):
comfy.model_management.unload_all_models()
need_gc = True
last_gc_collect = 0
if free_memory:
e.reset()
need_gc = True
last_gc_collect = 0
if need_gc:
current_time = time.perf_counter()
if (current_time - last_gc_collect) > gc_collect_interval:
gc.collect()
comfy.model_management.soft_empty_cache()
last_gc_collect = current_time
need_gc = False
hook_breaker_ac10a0.restore_functions()
if not asset_seeder.is_disabled():
asset_seeder.enqueue_enrich(roots=("output",), compute_hashes=True)
asset_seeder.resume()
async def run(server_instance, address='', port=8188, verbose=True, call_on_start=None):
addresses = []
for addr in address.split(","):
addresses.append((addr, port))
await asyncio.gather(
server_instance.start_multi_address(addresses, call_on_start, verbose), server_instance.publish_loop()
)
def hijack_progress(server_instance):
def hook(value, total, preview_image, prompt_id=None, node_id=None):
executing_context = get_executing_context()
if prompt_id is None and executing_context is not None:
prompt_id = executing_context.prompt_id
if node_id is None and executing_context is not None:
node_id = executing_context.node_id
comfy.model_management.throw_exception_if_processing_interrupted()
if prompt_id is None:
prompt_id = server_instance.last_prompt_id
if node_id is None:
node_id = server_instance.last_node_id
progress = {"value": value, "max": total, "prompt_id": prompt_id, "node": node_id}
get_progress_state().update_progress(node_id, value, total, preview_image)
server_instance.send_sync("progress", progress, server_instance.client_id)
if preview_image is not None:
# Only send old method if client doesn't support preview metadata
if not feature_flags.supports_feature(
server_instance.sockets_metadata,
server_instance.client_id,
"supports_preview_metadata",
):
server_instance.send_sync(
BinaryEventTypes.UNENCODED_PREVIEW_IMAGE,
preview_image,
server_instance.client_id,
)
comfy.utils.set_progress_bar_global_hook(hook)
def cleanup_temp():
temp_dir = folder_paths.get_temp_directory()
if os.path.exists(temp_dir):
shutil.rmtree(temp_dir, ignore_errors=True)
def setup_database():
try:
if dependencies_available():
init_db()
if args.enable_assets:
if asset_seeder.start(roots=("models", "input", "output"), prune_first=True, compute_hashes=True):
logging.info("Background asset scan initiated for models, input, output")
except Exception as e:
if "database is locked" in str(e):
logging.error(
"Database is locked. Another ComfyUI process is already using this database.\n"
"To resolve this, specify a separate database file for this instance:\n"
" --database-url sqlite:///path/to/another.db"
)
sys.exit(1)
if args.enable_assets:
logging.error(
f"Failed to initialize database: {e}\n"
"The --enable-assets flag requires a working database connection.\n"
"To resolve this, try one of the following:\n"
" 1. Install the latest requirements: pip install -r requirements.txt\n"
" 2. Specify an alternative database URL: --database-url sqlite:///path/to/your.db\n"
" 3. Use an in-memory database: --database-url sqlite:///:memory:"
)
sys.exit(1)
logging.error(f"Failed to initialize database. Please ensure you have installed the latest requirements. If the error persists, please report this as in future the database will be required: {e}")
def start_comfyui(asyncio_loop=None):
"""
Starts the ComfyUI server using the provided asyncio event loop or creates a new one.
Returns the event loop, server instance, and a function to start the server asynchronously.
"""
if args.temp_directory:
temp_dir = os.path.join(os.path.abspath(args.temp_directory), "temp")
logging.info(f"Setting temp directory to: {temp_dir}")
folder_paths.set_temp_directory(temp_dir)
cleanup_temp()
if args.windows_standalone_build:
try:
import new_updater
new_updater.update_windows_updater()
except:
pass
if not asyncio_loop:
asyncio_loop = asyncio.new_event_loop()
asyncio.set_event_loop(asyncio_loop)
prompt_server = server.PromptServer(asyncio_loop)
if args.enable_manager and not args.disable_manager_ui:
comfyui_manager.start()
hook_breaker_ac10a0.save_functions()
asyncio_loop.run_until_complete(nodes.init_extra_nodes(
init_custom_nodes=(not args.disable_all_custom_nodes) or len(args.whitelist_custom_nodes) > 0,
init_api_nodes=not args.disable_api_nodes
))
hook_breaker_ac10a0.restore_functions()
cuda_malloc_warning()
setup_database()
prompt_server.add_routes()
hijack_progress(prompt_server)
threading.Thread(target=prompt_worker, daemon=True, args=(prompt_server.prompt_queue, prompt_server,)).start()
if args.quick_test_for_ci:
exit(0)
os.makedirs(folder_paths.get_temp_directory(), exist_ok=True)
call_on_start = None
if args.auto_launch:
def startup_server(scheme, address, port):
import webbrowser
if os.name == 'nt' and address == '0.0.0.0':
address = '127.0.0.1'
if ':' in address:
address = "[{}]".format(address)
webbrowser.open(f"{scheme}://{address}:{port}")
call_on_start = startup_server
async def start_all():
await prompt_server.setup()
await run(prompt_server, address=args.listen, port=args.port, verbose=not args.dont_print_server, call_on_start=call_on_start)
# Returning these so that other code can integrate with the ComfyUI loop and server
return asyncio_loop, prompt_server, start_all
if __name__ == "__main__":
# Running directly, just start ComfyUI.
logging.info("Python version: {}".format(sys.version))
logging.info("ComfyUI version: {}".format(comfyui_version.__version__))
for package in ("comfy-aimdo", "comfy-kitchen"):
try:
logging.info("{} version: {}".format(package, importlib.metadata.version(package)))
except:
pass
if sys.version_info.major == 3 and sys.version_info.minor < 10:
logging.warning("WARNING: You are using a python version older than 3.10, please upgrade to a newer one. 3.12 and above is recommended.")
if args.disable_dynamic_vram:
logging.warning("Dynamic vram disabled with argument. If you have any issues with dynamic vram enabled please give us a detailed reports as this argument will be removed soon.")
event_loop, _, start_all_func = start_comfyui()
try:
x = start_all_func()
app.logger.print_startup_warnings()
event_loop.run_until_complete(x)
except KeyboardInterrupt:
logging.info("\nStopped server")
finally:
asset_seeder.shutdown()
cleanup_temp()
|