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

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.