Self Forcing | Autoregressive Keyframe-to-Video Generation

SUPER FAST! 5-second video in 45 seconds!

    **Who it's for:** creators who want this pipeline in ComfyUI without assembling nodes from scratch. **Not for:** one-click results with zero tuning — you still choose inputs, prompts, and settings.

    ### Open preloaded workflow on RunComfy
    [Open preloaded workflow on RunComfy (browser)](

    **Why RunComfy first**
    - **Fewer missing-node surprises** — run the graph in a managed environment before you mirror it locally.
    - **Quick GPU tryout** — useful if your local VRAM or install time is the bottleneck.
    - **Matches the published JSON** — the zip follows the same runnable workflow you can open on RunComfy.

    **When downloading for local ComfyUI makes sense** — you want full control over models on disk, batch scripting, or offline runs.

    **How to use (local ComfyUI)**
    1. Load inputs (images/video/audio) in the marked loader nodes.
    2. Set prompts, resolution, and seeds; start with a short test run.
    3. Export from the Save / Write nodes shown in the graph.

    **Expectations** — First run may pull **large weights**; cloud runs may require a **free RunComfy account**.

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    ### Overview
    Self Forcing trains autoregressive video diffusion models by simulating the inference process during training, performing autoregressive rollout with KV caching. It resolves the train-test distribution mismatch and enables real-time, streaming video generation on a single RTX 4090 while matching the quality of state-of-the-art diffusion models.

In simple terms, it allows you to generate smooth videos by providing start and end keyframe reference images along with a guiding text prompt, producing identity-consistent and motion-smooth video synthesis.

    ### Notes
    **Self Forcing | Autoregressive Keyframe-to-Video Generation** — see [RunComfy page]( for the latest node requirements.