PSA: Use the official LTX 2.3 workflow, not the ComfyUI included one. It's significantly better.

Most of the time I rely on the default ComfyUI workflows. They're producing results just as good as 90% of the overly-complicated workflows I see floating around online. So I was fighting with the default Comfy LTX 2.3 template for a while, just not getting anything good. Saw someone mention the official LTX workflows and figured I'd give it a try.

Yeah, huge difference. Easily makes LTX blow past WAN 2.2 into SOTA territory for me. So something's up with the Comfy default workflow.

If you're having issues with weird LTX 2 or LTX 2.3 generations, use the official workflow instead:

https://github.com/Lightricks/ComfyUI-LTXVideo/blob/master/example\_workflows/2.3/LTX-2.3\_T2V\_I2V\_Single\_Stage\_Distilled\_Full.json

This runs the distilled and non-distilled at the same time. I find they pretty evenly trade blows to give me what I'm looking for, so I just left it as generating both.

https://redd.it/1rz1u3j
@rStableDiffusion
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ComfyUI Nodes for Filmmaking (LTX 2.3 Shot Sequencing, Keyframing, First Frame/Last Frame)

https://redd.it/1rz355d
@rStableDiffusion
Nvidia SANA Video 2B



https://www.youtube.com/watch?list=TLGG-iNIhzqJ0OgyMDAzMjAyNg&v=7eNfDzA4yBs

Efficient-Large-Model/SANA-Video\_2B\_720p · Hugging Face

SANA-Video is a small, ultra-efficient diffusion model designed for rapid generation of high-quality, minute-long videos at resolutions up to 720×1280.

Key innovations and efficiency drivers include:

(1) Linear DiT: Leverages linear attention as the core operation, offering significantly more efficiency than vanilla attention when processing the massive number of tokens required for video generation.

(2) Constant-Memory KV Cache for Block Linear Attention: Implements a block-wise autoregressive approach that uses the cumulative properties of linear attention to maintain global context at a fixed memory cost, eliminating the traditional KV cache bottleneck and enabling efficient, minute-long video synthesis.

SANA-Video achieves exceptional efficiency and cost savings: its training cost is only 1% of MovieGen's (12 days on 64 H100 GPUs). Compared to modern state-of-the-art small diffusion models (e.g., Wan 2.1 and SkyReel-V2), SANA-Video maintains competitive performance while being 16× faster in measured latency. SANA-Video is deployable on RTX 5090 GPUs, accelerating the inference speed for a 5-second 720p video from 71s down to 29s (2.4× speedup), setting a new standard for low-cost, high-quality video generation.


More comparison samples here: SANA Video

https://redd.it/1rz153l
@rStableDiffusion
Training Lora with Ai Toolkit (about resolution)
https://redd.it/1rz5ifb
@rStableDiffusion
Have you tried fish audio S2Pro?

What is your experience with it? Do you think it can compete with Elevenlabs?
I have tried it and it is 80% as good as Elevenlabs.

https://redd.it/1rz7wjh
@rStableDiffusion