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    FisherKing-LTX2.3-[GGUF-Distilled]-T2V-ReferenceWorkflow-v1.0 [Low VRAM Compatible] - v1.0
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    Workflow Goal

    Provide a clean, educational reference implementation for LTX 2.3 Text-to-Video generation.

    This workflow focuses on simplicity, reproducibility, and education rather than including every available feature. It provides a tested baseline for generating high-quality cinematic videos directly from text prompts while remaining easy to understand, modify, and extend.

    Treat this workflow as a starting point and customize the prompt, and generation settings for your preferred artistic direction.

    Version 1.0

    Purpose

    ✓ Educational Reference Workflow

    ✓ Clean Baseline Implementation

    Features

    ✓ Wireless Modular Architecture

    ✓ Clean Reference Implementation

    ✓ Prompt Engineering Ready

    ✓ Two-Phase Sampling Pipeline

    ✓ Low VRAM Friendly

    ✓ Easy to Extend

    Workflow Pipeline

    Engine Configuration

    Video Clip Configuration

    Prompt Engineering

    Phase 1 Sampling (Audio & Video)

    (Generate motion at the base latent resolution.)

    2x Spatial Upscale

    (Increase latent spatial resolution.)

    Phase 2 Sampling (Audio & Video)

    (Recover fine spatial details after upscaling.)

    VAE Decode (Audio & Video)

    Final Video Output

    Verified Settings

    The following settings were used to validate this workflow and are recommended as the baseline configuration.

    Sampling

    ✓ CFG : 1.0

    ✓ Steps : 11 (8 + 3)

    ✓ Sampler : Euler Ancestral

    Video

    ✓ Frames : 145 (6 seconds @ 24 fps)

    ✓ Output FPS : 24 FPS

    ✓ Tested Resolution : 1024 × 576 (16:9)

    Required LoRA Configuration

    I have not used any specific lora in this test workflow

    Hardware & Resolution Notes

    Validated using:

    Hardware:

    RTX 2080 8 GB

    64 GB RAM

    Resolution:

    1024 × 576

    Length:

    6 seconds

    Generation Time:

    ~12–13 minutes

    Although compatible with 8 GB VRAM, LTX 2.3 Text-to-Video remains computationally intensive and memory hungry.

    System RAM is equally important for handling intermediate tensors and memory paging during video generation.

    Expected behavior:

    8 GB VRAM + 16 GB RAM

    Possible out-of-memory errors

    Slower generation

    8 GB VRAM + 32 GB RAM

    Better stability

    Performance depends on available system memory

    8 GB VRAM + 64 GB RAM (or more)

    Recommended configuration

    If your system have better GPUs, use 720p or higher resolutions

    Design Philosophy

    This workflow intentionally avoids unnecessary complexity.

    The objective is to provide a stable, reproducible reference implementation that users can understand, learn from, and extend for their own creative projects.

    I haven't added sage attention or other optimizations deliberately in this workflow.

    Description

    Workflows
    LTXV 2.3

    Details

    Downloads
    67
    Platform
    CivitAI
    Platform Status
    Available
    Created
    7/24/2026
    Updated
    7/27/2026
    Deleted
    -

    Files

    fisherkingLTX23GGUFDistilled_v10.json

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