# PromptMobile: Efficient Promptus for Low Bandwidth Mobile Video Streaming

arXiv: https://arxiv.org/abs/2503.16112 · HTML: https://mlsanity.com/paper/2503.16112/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 21 references that are in the map.
- First posted on arXiv 20 Mar 2025.

## Builds on (most cited first, 9 of 9)

- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Taming Transformers for High-Resolution Image Synthesis](https://mlsanity.com/paper/2012.09841/) (2020)
- [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://mlsanity.com/paper/1603.08155/) (2016)
- [Cache Me if You Can: Accelerating Diffusion Models through Block Caching](https://mlsanity.com/paper/2312.03209/) (2023)
- [Speed Is All You Need: On-Device Acceleration of Large Diffusion Models via GPU-Aware Optimizations](https://mlsanity.com/paper/2304.11267/) (2023)
- [CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streaming](https://mlsanity.com/paper/2211.08428/) (2022)
- [Reparo: Loss-Resilient Generative Codec for Video Conferencing](https://mlsanity.com/paper/2305.14135/) (2023)
- [Promptus: Can Prompts Streaming Replace Video Streaming with Stable Diffusion](https://mlsanity.com/paper/2405.20032/) (2024)
- [Accelerating Mobile Edge Generation (MEG) by Constrained Learning](https://mlsanity.com/paper/2407.07245/) (2024)

## Abstract (arXiv)

Traditional video compression algorithms exhibit significant quality degradation at extremely low bitrates. Promptus emerges as a new paradigm for video streaming, substantially cutting down the bandwidth essential for video streaming. However, Promptus is computationally intensive and can not run in real-time on mobile devices. This paper presents PromptMobile, an efficient acceleration framework tailored for on-device Promptus. Specifically, we propose (1) a two-stage efficient generation framework to reduce computational cost by 8.1x, (2) a fine-grained inter-frame caching to reduce redundant computations by 16.6%, (3) system-level optimizations to further enhance efficiency. The evaluations demonstrate that compared with the original Promptus, PromptMobile achieves a 13.6x increase in image generation speed. Compared with other streaming methods, PromptMobile achives an average LPIPS improvement of 0.016 (compared with H.265), reducing 60% of severely distorted frames (compared to VQGAN).