PrunaVAED directly replaces the video VAE decoder in
diffusers/LTX-2.3-Diffusers.
The encoder and latent format remain unchanged, making it a drop-in upgrade
for faster, more memory-efficient LTX-2.3 decoding.
Examples
Both columns decode the same LTX-2.3 latent from the distilled pipeline.
Benchmark
Metrics compare videos decoded from the same latents by the LTX-2.3 VAED and PrunaVAED. Two set of latents were
generated with the full
ti2vid_two_stages
pipeline and the
distilled
pipeline (recommended).
* Tiling required on H100; 14533ms otherwise
Δ-frame PSNR is PSNR on consecutive-frame differences (temporal consistency).
Quickstart
End-to-end smoke demo: generate a short video with the diffusers LTX-2.3 distilled two-stage pipeline, then decode the same latent with the stock LTX-2.3 VAE and with PrunaVAED. Writes two mp4s and prints decode time (ms). Needs a CUDA GPU.
# 1. Install the Hugging Face CLI
pip install hf
# 2. Download this repo
hf download PrunaAI/PrunaVAED --local-dir PrunaVAED
cd PrunaVAED
# 3. Install dependencies
pip install -r requirements-demo.txt
# 4. Run the demo (~1080p, ~5 s @ 24 fps)
python demo/demo_distilled_decode.py
Outputs land in outputs/demo_distilled/ (ltx23.mp4, prunavaed.mp4).
Edit PROMPT / resolution at the top of demo/demo_distilled_decode.py if needed.
Architecture
PrunaVAED is bitwise identical to LTX 2.3 VAED from conv_in to up_blocks.0. Pruning starts
at up_blocks.1.
| Stage | Channel reduction |
|---|---|
up_blocks.0 | unchanged |
up_blocks.1 | 25% |
up_blocks.2 | 50% |
up_blocks.3 | 50% |
| Teacher (LTX-2.3) | PrunaVAED | |
|---|---|---|
| Encoder params | 318.9 M | 318.9 M (unchanged) |
| Decoder params | 407.2 M | 345.0 M (−15%) |
| Total VAE params | 726.1 M | 663.9 M |
prunavaed/patch_diffusers.py provides the required compatibility shim for
the pinned diffusers version.
Limitations
- Evaluated on 4-second clips at 24 fps.
- Benchmarked on one H100 80GB with bfloat16 and batch size 1.
- Speed and VRAM vary with hardware, resolution, batch size, and software.
- Evaluated only on two differents pipeline of LTX 2.3 (
ti2vid_two_stagespipeline and thedistilled) - The weights can be adapted to the custom
LTX-2library without retraining, but no implementation is provided for this yet.
What this is not
- Not a full T2V model.
- Not a replacement for the LTX denoiser/generator.
- Not compatible with arbitrary VAE latents.
- Not bit-exact with the original decoder.
License
PrunaVAED is a derivative of LTX-2.3 and is distributed under the LTX-2 Community License Agreement. Review its use restrictions and commercial terms before using or redistributing the model.
Helper code adapted from Hugging Face diffusers retains its Apache-2.0
attribution; see NOTICE.
What's next?
- Use PrunaVAED to speed up LTX-2.3 decoding.
- Compress your own models with Pruna and give us a ⭐️ for more efficiency!
- Want to use our optimized video model right away? Check P-Video and P-Video documentation.
Try our models