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Cover image for LTX 2 & Z Image Base Full Tutorial + Audio to Video Lip Sync + ComfyUI + SwarmUI + Windows + Cloud
Furkan Gözükara
Furkan Gözükara

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LTX 2 & Z Image Base Full Tutorial + Audio to Video Lip Sync + ComfyUI + SwarmUI + Windows + Cloud

#ai #tutorial #opensource #news

LTX 2 & Z Image Base Full Tutorial + Audio to Video Lip Sync + ComfyUI + SwarmUI + Windows + Cloud

Full tutorial link > https://www.youtube.com/watch?v=SkXrYezeEDc

Info

LTX 2 is the newest state of the art (SOTA) Open Source video generation model and tutorial will show you how to use it with very best and most performant way in ComfyUI and also in SwarmUI. Moreover, Z Image Base model published and I will show how to use Z Image Base with most amazing preset and workflow as well. Furthermore, this tutorial will show you how to install, update, setup, download ComfyUI and SwarmUI and models and presets and workflows both on Windows and on RunPod, Massed Compute and SimplePod. Linux users can use Massed Compute scripts and installers directly. This is a masterpiece entire lecture level complete tutorial. This video will kickstart your AI journey 100x. Both local Windows and Cloud.

📂 Resources & Links:

⏱️ TIMESTAMPS

  • 00:00:00 Intro: ComfyUI + SwarmUI presets, Z-Image, model downloader, cloud installs

  • 00:00:28 Free prompt enhancement with Google AI Studio (prepared prompt file)

  • 00:01:26 Demo: 45s audio-driven lip-sync image→video (LTX 2)

  • 00:02:25 Quick demos: ComfyUI image→video, text→video, Z-Image base

  • 00:03:43 Quick demos: SwarmUI LTX 2 image→video + Z-Image base

  • 00:04:46 Install/update presets zip (v78+): extract & overwrite everything

  • 00:05:11 Upgrade to CUDA 13 safely: delete venv then run ComfyUI update/install

  • 00:06:00 Windows prereqs + the always-updated setup guide referenced in description

  • 00:06:42 Install required node bundles: (1) SwarmUI extra nodes + (100) LTX audio

  • 00:07:29 VRAM-optimized launcher: no-VRAM / cache / smart-memory / precision choices

  • 00:09:36 Share one model library: configure extra_model_paths.yaml (no duplicates)

  • 00:10:25 Model Downloader overview: set base path + one-click bundles for SwarmUI/ComfyUI

  • 00:11:43 Download LTX 2 core bundle: multi-connection download + merge + hash verify

  • 00:12:12 Low-VRAM path: GGUF distilled models vs recommended FP8-scaled defaults

  • 00:14:16 URL Downloader: Civitai/HF links, folder targeting, and optional API keys

  • 00:14:54 ComfyUI preset pack tour: LTX2 (I2V/T2V/audio) + Z-Image (base/2× upscale)

  • 00:15:16 ComfyUI audio lip-sync preset: image + resolution + audio setup

  • 00:16:58 Frames & prompting: 24fps math, run/stop frame count, lyrics/subtitles prompts

  • 00:17:59 Quality/perf knobs: CRF, VRAM monitoring, and low-VRAM args recap

  • 00:20:22 Review result + move to LTX 2 image→video preset workflow

  • 00:21:50 Prompt enhancer workflow: drag prompt file into AI Studio (optionally add image)

  • 00:24:11 Z-Image troubleshooting: disable Sage Attention and restart

  • 00:24:32 Z-Image base + 2× upscale preset: when to use it and what to expect

  • 00:26:47 Outputs & reproducibility: where renders save + drag PNG to reload metadata

  • 00:27:57 Update SwarmUI via zip: get latest presets + utilities

  • 00:28:27 SwarmUI setup: ComfyUI backend, passing args, and pointing to model folders

  • 00:30:21 SwarmUI image→video: direct apply + init image workflow

  • 00:31:17 Fix model load/caching issues: add --use-cache-none when needed

  • 00:32:51 SwarmUI text→video + upscale: duration/frames, half-res then upscale rules

  • 00:33:52 SwarmUI outputs: output_local/raw + metadata saved with generations

  • 00:35:05 SwarmUI Z-Image: base vs 2× upscale comparison + speed notes

  • 00:36:58 Image comparison slider tool: quick before/after inspection

  • 00:37:51 RunPod start: template choice, CUDA/driver constraints, optional storage volume

  • 00:43:30 RunPod Jupyter: upload ComfyUI zip, extract, install bundles (1+100)

  • 00:46:28 RunPod: run Model Downloader, start ComfyUI, connect via exposed port

  • 00:52:05 RunPod: switch to SwarmUI, map folders (case-sensitive), import presets

  • 00:55:43 RunPod: download outputs as archive + stop vs terminate cost control

  • 00:57:55 SimplePod: cheaper/faster alternative + persistent volume setup highlights

  • 01:03:52 Massed Compute: deploy with coupon + connect via ThinLinc (shared folder setup)

  • 01:08:17 Massed Compute: install bundles + download models (disk speed advantage)

  • 01:10:48 Massed Compute: start ComfyUI, connect from PC, run lip-sync preset

  • 01:14:26 Massed Compute: hook SwarmUI to ComfyUI backend + text→video demo

  • 01:17:02 Wrap-up: recap providers + next steps

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