Model reference · open weights
SoulX-FlashHead-1 is an open-weight video model from Soul-AILab. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | Soul-AILab |
|---|---|
| Type | Video models |
| Task | Image→video |
| Runs with | diffusers |
| Released | 2026-02-11 |
| Popularity | 2k downloads / month |
| Licence | Open weights |
About
Soul-AILab/SoulX-FlashHead-1_3B
Tan Yu*, Qian Qiao*✉, Le Shen*, Ke Zhou, Jincheng Hu, Dian Sheng, Bo Hu, Haoming Qin, Jun Gao, Changhai Zhou, Shunshun Yin, Siyuan Liu ✉
More examples are available in the project.
conda create -n flashhead python=3.10
conda activate flashhead
pip install torch==2.7.1 torchvision==0.22.1 --index-url https://download.pytorch.org/whl/cu128
pip install -r requirements.txt
pip install ninja
pip install flash_attn==2.8.0.post2 --no-build-isolation
-- If it takes a long time, we recommend the way below.
pip install sageattention==2.2.0 --no-build-isolation
# Ubuntu / Debian
apt-get install ffmpeg
# CentOS / RHEL
yum install ffmpeg ffmpeg-devel
or
# Conda (no root required)
conda install -c conda-forge ffmpeg==7
# If you are in china mainland, run this first: export HF_ENDPOINT=https://hf-mirror.com
pip install "huggingface_hub[cli]"
huggingface-cli download Soul-AILab/SoulX-FlashHead-1_3B --local-dir ./models/SoulX-FlashHead-1_3B
huggingface-cli download facebook/wav2vec2-base-960h --local-dir ./models/wav2vec2-base-960h
# Infer with [Pro-Model] on single GPU
bash inference_script_single_gpu_pro.sh
# Infer with [Pro-Model] on multy GPUs
bash inference_script_multi_gpu_pro.sh
# Real-time inference speed of Pro-Model can only be supported on two RTX-5090 with SageAttention.
# Infer with [Lite-Model] on single GPU
bash inference_script_single_gpu_lite.sh
# Real-time inference speed can be supported on single RTX-4090 (up to 3 concurrent).
For a real-time interactive experience, scan the QR code to enter the event link. [2026.2.12~2026.3.11]
If you are interested in leaving a message to our work, feel free to email yutan@soulapp.cn or qiaoqian@soulapp.cn or le.shen@mail.dhu.edu.cn or zhouke@soulapp.cn or liusiyuan@soulapp.cn
We have opened a WeChat group. Additionally, we represent SoulApp and warmly welcome everyone to download the app and join our Soul group for further technical discussions and updates!
If you find our work useful in your research, please consider citing:
@misc{yu2026soulxflashheadoracleguidedgenerationinfinite,
title={SoulX-FlashHead: Oracle-guided Generation of Infinite Real-time Streaming Talking Heads},
author={Tan Yu and Qian Qiao and Le Shen and Ke Zhou and Jincheng Hu and Dian Sheng and Bo Hu and Haoming Qin and Jun Gao and Changhai Zhou and Shunshun Yin and Siyuan Liu},
year={2026},
eprint={2602.07449},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2602.07449},
}
[!TIP] If you find our work useful, please also consider starring the original repositories of these foundational methods.
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys soulx-flashhead-1 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (soulx-flashhead-1 below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/videos/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"soulx-flashhead-1","prompt":"a drone shot over a forest"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.