Abiray/LTX-2.5-Distilled-GGUF
text-to-video model by Abiray
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
This repository provides quantized GGUF formats of the distilled transformer from Lightricks/LTX-2.5. These weights are highly optimized for local execution, allowing you to run high-fidelity video and audio generation workflows on hardware with memory constraints while retaining the core visual fidelity of the original base model. LTX-2.5 operates on a split-component architecture. To run these GGUF diffusion models in environments like ComfyUI or local Python pipelines, you must also fetch the official Text Encoders and VAEs directly from the upstream Lightricks/LTX-2.5 repository. Download these from the textencoders directory: Download these from the vae directory: To achieve maximum visual fidelity and smoothness, it is highly recommended to use the official Stage 2 latent upscalers alongside this GGUF model. You can download them from the official Lightricks LTX-2.5 Repository here. To make running this GGUF model as plug-and-play as possible, I have included two pre-configured ComfyUI workflows in this repository. You can…
Read the full model card ↗ · Preview checked 2026-10-28T04:06:50.665Z
Inside the original model card — Document outline
- LTX-2.5 Distilled GGUF
- Available Quantizations
- Required Supporting Components (Text Encoders & VAEs)
- Text Encoders
- VAEs (Video & Audio)
- 📈 Latent Upscalers (Recommended)
- Available Upscaler Models
- ComfyUI T2V and I2V GGUF Workflows
- About the Original Model
- Key Features of LTX-2.5
- Usage Requirements
- License & Limitations
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Documentation belongs to its respective authors. Reported project/model license: other. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
Abiray/LTX-2.5-Distilled-GGUF is a text-to-video model repository published by Abiray on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-video
- Library
- Not reported
- Recent downloads (30 days)
- 51,007
- Cumulative likes
- 87
- Hugging Face trending score
- 2
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-08-12T04:59:29.000Z
- Last modified
- 2026-08-22T08:14:31.000Z
Compatibility and lineage
Reported languages: en, de, es, fr, ja, ko, zh, it, pt
Reported base models: Lightricks/LTX-2.5
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:32.159Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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