📂 DOWNLOAD THE LTX 2.3 v 1.1 8GB VRAM I2V WORKFLOW : https://drive.google.com/file/d/1GMMK...
📂 RTX Super Resolution Upscaling Workflow: https://drive.google.com/file/d/1g3fI...
Running high-quality local AI video generation on an 8GB VRAM setup is entirely possible with a highly optimized workflow. This technical breakdown covers the LTX 2.3 v1.1 update, focusing specifically on a stable image-to-video ComfyUI pipeline that fully supports complex LoRAs without triggering out-of-memory errors.
We explore the current reality of temporal consistency in AI video models and how to implement specific transition tools, like the Henshin transformation LoRA, to guide your animations accurately. You will see how integrating the FP8 model version with Sage Attention 2.2 drastically cuts down SSD swapping, keeping your memory usage strictly within the VRAM and system RAM limits. For users with different hardware architectures, we also outline stable GGUF alternatives to maintain visual fidelity.
All models, including the transition LoRAs mentioned in the tutorial, go straight into your ComfyUI LoRAs folder.
Hardware utilized for this workflow:
Laptop: Gigabyte A16
GPU: Nvidia RTX 5060 (8GB VRAM)
System RAM: DDR5 32GB
If this workflow helps streamline your local AI video generation, a thumbs up goes a long way in supporting the Tensor Alchemist community. Joining the channel ensures you catch all upcoming 8GB VRAM optimization guides, node breakdowns, and generative AI tutorials.
Timestamps:
0:00 - What's in the video?
0:36 - I2V Workflow Request
0:52 - Disclaimer! Issues of LTX 2.3 I2V
2:20 - i2v previews (No LoRAs)
3:15 - Transformation LoRA
4:27 - Live Generation
5:00 - FP8, Sage Attention, GGUFs
5:47 - Transition LoRA
7:00 - Other LoRAs
7:08 - Workflow
#ltx23 #comfyui #aivideo #stablediffusion #machinelearning #generativeai #artificialintelligence #gpuoptimization #localai #tensoralchemist #techstack