LTX 2.5 GGUF ComfyUI | Image-to-Video with Synced Audio - v1.0 Showcase
LTX-2.5 GGUF turns images into cinematic videos with synced audio.
Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning - you still choose inputs, prompts, and settings.
Open preloaded workflow on RunComfy
Open preloaded workflow on RunComfy (browser)
Why RunComfy first
- Fewer missing-node surprises - run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout - useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON - the zip follows the same runnable workflow you can open on RunComfy.
When downloading for local ComfyUI makes sense - you want full control over models on disk, batch scripting, or offline runs.
How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.
Expectations - First run may pull large weights; cloud runs may require a free RunComfy account.
Overview
Turn a source image into a short cinematic video. Guide character, machine, or environmental motion with a text prompt. Generate synchronized audio for each shot. Use LTX-2.5 GGUF inference to reduce memory demands. Add latent upscaling for cleaner results. Create faster with the ready-made graph.
Important nodes:
Key nodes in ComfyUI LTX 2.5 GGUF ComfyUI workflow
UnetLoaderGGUF (#406)
Loads the LTX‑2.5 distilled UNet in GGUF format. Choose the quantized file that matches your VRAM budget; lighter quantization lowers memory and speeds up inference at some quality cost. If you upgrade to a less‑quantized file, expect sharper textures and more stable fine motion.
LTXVImgToVideoInplace (#357 and #349)
Injects the first frame into the latent so motion evolves from your image rather than drifting away. Toggle the bypass input when switching between image‑to‑video and text‑to‑video. Use the low‑res node (#357) for initial stabilization and the high‑res node (#349) to re‑anchor details after upscaling.
LTXVLatentUpsampler (#348)
Applies the LTX‑2.5 Latent Spatial Upscaler to add detail without decoding to pixels. Use it when you want more definition at nearly the same memory cost as the coarse pass. If you see flicker after upscaling, slightly strengthen guidance in the following refinement stage.
ManualSigmas (#397 and #396)
Controls the denoise schedule used by the samplers. Shorter schedules are faster but can reduce adherence or temporal smoothness; longer or front‑loaded schedules add stability at extra cost. Pair this with the sampler choice to balance speed and quality for your scene.
VAEDecodeTiled (#374)
Decodes the high‑res video latent to frames using tiles to cap VRAM usage. If you run out of memory, reduce tile size or enable stronger tiling; if you see seams, increase overlap or try a larger tile. Keep your VAE selection aligned with the official LTX‑2.5 video VAE.
CreateVideo (#370)
Muxes the image sequence and decoded audio into a final video file. Set fps to match your generation frame rate to avoid time stretch. Use this as the single render point for consistent outputs across iterations.
Notes
LTX 2.5 GGUF ComfyUI | Image-to-Video with Synced Audio - see RunComfy page for the latest node requirements.