CivArchive
    WAN 2.2 S2V 14B GGUF - Wan2.2-S2V-14B Q6
    NSFW

    Wan-S2V is an AI video generation model that can transform static images and audio into high-quality videos.

    WIP: working on description adding all needed infos/tools! Use with some caution 🤪

    Note: S2V has a very high chance of producing some 1st "flashy" over-saturated frames. That seems a limitation of all Wan 2.2 S2V models right now.

    Requirements:

    • lite lora for 4/8-step operation (optional)

    • Main Model Wan2.2-S2V-14B ComfyUI/models/unet GGUF

    • Audio Encoder wav2vec2_large_english ComfyUI/models/audio_encoders

    • Encoder Umt5-xxl ComfyUI/models/text_encoders

    • Wan2.1_VAE.safetensors ComfyUI/models/vae

    Usage hints:

    • Audio file should be about same length as the video file in seconds

    👂🎶 👉 Hint: Click the sample for full-screen and play from the post with SOUND ON!

    Sources:

    Clip: https://huggingface.co/city96/umt5-xxl-encoder-gguf/

    Model: https://huggingface.co/QuantStack/Wan2.2-S2V-14B-GGUF/

    Lite LoRA: https://huggingface.co/calcuis/wan2-gguf/

    YOU are responsible for outputs as always! If you make ToS violating content and I get aware I WILL report this.

    Description

    FAQ

    Comments (1)

    blobby99Sep 1, 2025· 6 reactions
    CivitAI

    Remember, with Blackwell (and maybe earlier architectures) do NOT use scaled FP8 models- these massively downgrade prompt adherence and lip movement. Even a smaller GGUF Clip or main model will work much better- even with a gofaster LoRA.

    This workflow does uses GGUF for both, in the mistaken understanding that small models are needed for 'low' VRAM like 12-16GB - no, so long as you have enough system RAM to cache the model, the slow iteration times (many times greater than 1 second) allow the model to stream as needed with no impact on iteration speed!

    Checkpoint
    Wan Video 2.2 I2V-A14B
    by darksidewalker

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    base model

    Details

    Downloads
    179
    Platform
    CivitAI
    Platform Status
    Deleted
    Created
    8/31/2025
    Updated
    6/2/2026
    Deleted
    11/22/2025

    Files

    wan22S2V14BGGUF_wan22S2V14BQ6.gguf

    Size:
    15.10 GB
    SHA256:
    b9a304b4431ee8da5bc52eb9d01f6e953a2f1323b44ec597f35172ac0a0754a7

    Mirrors

    CivitAI (1 mirrors)

    Available On (1 platform)

    Same model published on other platforms. May have additional downloads or version variants.

    SeaArt
    WAN 2.2 S2V 14B GGUF - Wan2.2-S2V-14B Q6