The FASTEST local AI video generator
LTX 2.5 gives indie filmmakers an ultra-fast local option for 4K video generation and shot extension that bypasses high API credit costs.
What this lesson covers
This tutorial demonstrates how to install and run Lightricks' open-source LTX 2.5 model locally inside ComfyUI. LTX 2.5 features diffusion fidelity rendering, multi-shot generation, and a two-pass architecture that combines fast low-resolution generation with a spatial upscaler to achieve rapid 4K output.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:24 ↗
LTX 2.5 uses diffusion fidelity rendering to dynamically allocate compute based on scene complexity rather than wasting steps on static areas.
- 00:50 ↗
The model supports multi-shot video generation within a single render pass while maintaining character and environment consistency.
- 03:34 ↗
Choosing the distilled INT8 or FP4 quantized diffusion models allows LTX 2.5 to execute generations in 4-6 steps on mid-tier GPUs.
- 07:05 ↗
LTX 2.5 achieves its high render speeds by performing an initial low-resolution pass before processing through a dedicated spatial upscaler.
Workflow outlined in the video
- Update ComfyUI to the latest version to ensure built-in template compatibility with LTX 2.5 workflows.
- Download the LTX 2.5 distilled INT8 diffusion model, Gemma 4 text encoder, audio/video VAEs, and spatial upscaler into their respective ComfyUI model directories.
- Load the native LTX 2.5 text-to-video or image-to-video ComfyUI templates and configure duration and frame rate settings.
- Disable prompt enhancer nodes to conserve local VRAM and speed up render iterations.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
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How to interpret the numbers
157,483 views captured 27 September 2026. ReelStack recommendation score: 46/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 1.05× views vs 9 other channel videos observed at a similar age. View-evidence factor 99% (views / (views + 1,000))
- 25% freshness: 14/100 with a 14-day half-life
- 20% momentum: 926 views/day vs 388 channel baseline (6 comparable uploads), with the same view-evidence factor
- 10% engagement: 59/100; likes + 4× comments, smoothed with a 500-view neutral prior