Automate AI video generation using ComfyUI + LTX-2.3 model. Ideal for music video (MV) production, multi-scene batch rendering, and AI video content creation.

Requirements

Item	Spec
GPU	≥24GB VRAM (Turing/Ampere/Ada)
ComfyUI	0.17+
PyTorch	2.6+cu124
Access	SSH tunnel forwarding port 18188

Model Setup

Model	Size	Path
LTX-2.3 dev (bf16)	43GB	models/checkpoints/ltx-2.3-22b-dev.safetensors
Gemma 3 12B	23GB	models/text_encoders/comfy_gemma_3_12B_it.safetensors
Distilled LoRA	7.1GB	models/loras/ltxv/ltx2/ltx-2.3-22b-distilled-lora-384.safetensors
Video VAE (bf16)	-	models/vae/LTX23_video_vae_bf16.safetensors

Turing GPUs (e.g., Quadro RTX 8000) do NOT support fp8_e4m3fn. Use bf16/fp16 models only.

Performance Baseline

Per-step time: ~221s (constant, regardless of frame count!)
15 steps: ~57 min
25 steps: ~1h45m
Frames: 72=3s, 121=5s, 480=20s (24fps)

Key insight: Frame count does NOT affect total time. Bottleneck is model forward pass.

Workflow Node Reference

Node	ID	Purpose
LoadImage	2004	I2V reference input
CLIPTextEncode (positive)	2483	Positive prompt
CLIPTextEncode (negative)	2612	Negative prompt
EmptyLTXVLatentVideo	3059	Empty latent
LTXVScheduler	4966	Steps/length params
LoraLoaderModelOnly	4922+	LoRA loader
SaveVideo	4823/4852	Output mp4

Quick Start

Generate a Single Video (I2V)

• Load workflow: /workspace/ComfyUI/custom_nodes/ComfyUI-LTXVideo/example_workflows/2.3/LTX-2.3_T2V_I2V_Single_Stage_Distilled_Full.json
• Set params using scripts/batch_scenes.js
• Click Run
• Wait ~1 hour
• Download from /workspace/ComfyUI/output/

Batch Scene Generation

Use scripts/batch_scenes.js for automation:

// Load script first, then configure each scene:
await comfyui_batch.configureScene({
  name: "scene_01",
  prompt: "A lonely girl running through rain at night, neon reflections",
  image: "unified_ref.png",
  steps: 15,
  frames: 72
});
// Click Run, repeat for next scene

Step Count Guide

Steps	Quality	Time/Scene	Use Case
8	Rough	~30min	Quick preview
15	Good	~57min	Recommended sweet spot
25	Best	~1h45m	Final quality output

I2V + LoRA at 15 steps achieves ~90% of 25-step quality with 40% less time.

Troubleshooting

VAEDecode Validation Failed

Error: Exception when validating node: 'VAEDecode' Cause: VAE load timing or insufficient VRAM Fix: Reload the entire workflow (fetch + loadGraphData), wait for models to fully load, then run. Never reload during execution.

Browser Tab Lost

Cause: SSH tunnel disconnected Fix:

• Rebuild tunnel: ssh -f -N -L 18188:localhost:18188 user@host -p port
• Navigate to ComfyUI
• Reload workflow

Inconsistent Characters Across Scenes

Cause: Different reference images per scene Fix: Use the SAME reference image for all scenes. Extract a clear frame from an existing video if needed. The I2V input image dictates the visual baseline.

Output Video Not Saved

Check: ssh -p PORT root@HOST "ls -lht /workspace/ComfyUI/output/.mp4" Fix: Check for VAEDecode errors in log, then re-run.

Monitoring Progress

# Current sampling progress
ssh -p PORT root@HOST "grep 'it/s' /tmp/comfy.log | tail -1"
# Completion check
ssh -p PORT root@HOST "grep 'Prompt executed' /tmp/comfy.log | tail -1"
# Output files
ssh -p PORT root@HOST "ls -lht /workspace/ComfyUI/output/.mp4"

Best Practices

• 15 steps is the sweet spot — I2V converges at 15-20 steps, 25 has diminishing returns
• Unified reference image — Same input image for all scenes ensures character consistency
• Reload workflow every time — Avoids VAEDecode validation failures
• Never reload during execution — Current run will fail
• Frame selection — 72 frames (3s) for testing, 480 frames (20s) for final output
• VRAM management — Wait for each generation to complete before starting next

T2V vs I2V Comparison

Mode	Steps	Quality	Notes
T2V (no LoRA)	15	❌ Very blurry	Not recommended
I2V + LoRA	25	✅ Excellent	Major quality improvement
I2V + LoRA	15	✅ Very good	Best time/quality ratio

Conclusion: I2V + LoRA is the recommended combination.

Resources

• scripts/batch_scenes.js — Batch scene automation
• references/workflow_nodes.md — Full node ID mapping
• references/tips.md — Prompt tips, VRAM management, optimization