(Down)Load DynamiCrafterModel

This is where a DynamiCrafter or ToonCrafter workflow starts. It's the loader node: pick a checkpoint from the dropdown, and if you don't already have the file, it downloads it for you and hands the loaded model down the graph. The "(Down)Load" in the name is the whole pitch - no hunting for the right HuggingFace file, no guessing the filename, no renaming a .ckpt. Pick from the list, run, done.

It comes from kijai's ComfyUI-DynamiCrafterWrapper, and if you've spent any time in ComfyUI you already know the pattern. Kijai is the person who wraps a fresh research repo - IC-Light, DepthAnythingV2, MoGe, LivePortrait, half the LTX and Wan tooling - into clean ComfyUI nodes, usually within days of the paper dropping. This pack wraps two related models out of CUHK / Tencent AI Lab: DynamiCrafter (animate a still image into a short clip) and ToonCrafter (the cartoon-interpolation variant that briefly had r/StableDiffusion convinced indie anime was solved). Both need a checkpoint, and this node is how you get one.

How it works

The auto-download nodes in Kijai's packs point at his own pruned, converted HuggingFace repos rather than the original research releases. The originals ship as fat .ckpt files that need renaming to specific names before the wrapper will touch them. Kijai re-exported them to bf16 .safetensors, pruned the dead weight, and wired the filenames straight into this dropdown. First run pulls the file into ComfyUI/models/checkpoints; every run after that just loads it. If you'd rather manage the file yourself, DynamiCrafterModelLoader is the bring-your-own-checkpoint sibling.

The inputs and outputs that matter

Three inputs, and really only two decisions:

• model - the dropdown. This is the choice that defines your whole workflow. Names starting tooncrafter_ are for cartoon interpolation (feed them to ToonCrafterInterpolation). The dynamicrafter_512/dynamicrafter_1024 ones are general image-to-video; the _interp ones do start/end-frame interpolation and looping. The CIL variants are watermark-free re-trains. Match the model to the task - a ToonCrafter checkpoint in an I2V graph, or vice versa, just gives you mush.
• fp8_unet - flip this to true to run the UNet in fp8 and shave 1-2GB off VRAM. On a tight card it's the difference between fitting and OOMing; quality cost is small.
• dtype - leave it on auto unless you have a specific reason. It picks fp16/bf16 based on your hardware.

The single output is DynCraft_model (type DCMODEL). That wire is the backbone of the graph - it feeds DynamiCrafterI2V, ToonCrafterInterpolation, DynamiCrafterBatchInterpolation, ToonCrafterDecode, and DynamiCrafterLoadInitNoise. Everything downstream wants it.

Installing it

The node ships with the pack. Grab it in ComfyUI Manager by searching ComfyUI-DynamiCrafterWrapper, or from a terminal: cd ComfyUI/custom_nodes && git clone https://github.com/kijai/ComfyUI-DynamiCrafterWrapper, then pip install -r requirements.txt (portable users point at python_embeded\python.exe -m pip). Restart ComfyUI. Kijai's README also strongly recommends installing xformers (pip install xformers --no-deps) - without it, memory use on these models is huge, and ToonCrafter's decode leans on it hard.

Common issues

• First run "hangs." It's downloading a multi-gigabyte checkpoint with no fat progress bar in the node. Watch the console. This is a one-time cost per model.
• Picked the wrong checkpoint. The single most common mistake: a dynamicrafter model wired into a ToonCrafter node, or the non-_interp model in an interpolation graph. Read the dropdown name against what your downstream node expects.
• Still OOMs with fp8 on. These are 2024-era video models and they're memory-hungry by today's standards. Drop your resolution and frame count, make sure xformers is actually installed, and remember the decode step (not sampling) is usually the peak.