--- license: apache-2.0 library_name: audio.cpp base_model: Soul-AILab/SoulX-FlashHead-1_3B base_model_relation: quantized tags: - audio.cpp - gguf - talking-head - image-to-video - audio-to-video --- # SoulX-FlashHead Lite GGUF Follow or star [audio.cpp](https://github.com/0xShug0/audio.cpp) for the C++ runtime and model integration updates. GGUF packaging of [Soul-AILab/SoulX-FlashHead-1_3B](https://huggingface.co/Soul-AILab/SoulX-FlashHead-1_3B/tree/5fbd2e44ba08ab2deb28bd55cff2c15523e51ba5). The model generates streaming talking-portrait video from a reference image and speech audio. This repository packages **Lite** only, including its DiT, LTX video VAE and [Wav2Vec2 speech encoder](https://huggingface.co/facebook/wav2vec2-base-960h). Upstream checkpoint revision: `5fbd2e44ba08ab2deb28bd55cff2c15523e51ba5`. Model architecture and weights are by Soul-AILab; the C++ integration is in audio.cpp. > [!IMPORTANT] > **cuDNN is strongly recommended for CUDA: about 2× faster warm inference, with lower peak VRAM.** > **Prebuilt audio.cpp binaries do not include cuDNN support.** Build from source > with cuDNN and `-DGGML_CUDA_CUDNN_CONV3D=ON`, then select > `--session-option 'soulx_flashhead.exec_plan={"vae":{"impl":"cudnn"}}'`. > The default GGML path remains available without cuDNN, including in prebuilts. ## English streaming demo Generated from a single reference portrait and 42.24 seconds of English narration using audio.cpp: Lite Q8, 512×512, four denoising steps, 25 FPS, Vulkan backend. Audio is processed in 0.96-second chunks with continuous motion between chunks. Inputs: [English audio](demo/english.wav), [transcript](demo/english.txt), and [portrait](demo/portrait.png). The portrait is from the [upstream example](https://github.com/Soul-AILab/SoulX-FlashHead/blob/main/examples/girl.png). The English narration was generated with Qwen3-TTS. ## audio.cpp CUDA performance Measured on an RTX 5090 with the Q8 package, 512×512 output, four denoising steps, and the 42.24-second English demo above (44 streaming chunks). Debug build, eight CPU threads; the two modes were run sequentially. | VAE implementation | Warm RTF ↓ | Full-run RTF ↓ | Peak VRAM | |---|---:|---:|---:| | cuDNN (recommended) | 0.215 | 0.430 | 5,168 MiB | | GGML (default) | 0.490 | 0.706 | 9,152 MiB | RTF is generation time divided by video duration; lower is faster. Warm RTF covers the full audio-encoder, DiT, VAE, color-correction and RGB-output pipeline, excluding the first two chunks and CLI artifact serialization. Full-run RTF also includes initialization, cold chunks and CLI artifact serialization. Both exclude model loading and MP4 encoding. Peak VRAM is sampled per-process GPU memory. The cuDNN VAE uses F16 activations with F32 accumulation. ## Weights and usage | File | Components | |---|---| | `SoulX-FlashHead-Lite-Q8_0.gguf` | Q8 DiT, BF16 LTX VAE, F32 Wav2Vec2, embedded configuration and model contract | | `SoulX-FlashHead-Lite-BF16.gguf` | BF16 DiT and LTX VAE, F32 Wav2Vec2, embedded configuration and model contract | ```bash audiocpp_cli --family soulx_flashhead --task gen \ --model SoulX-FlashHead-Lite-Q8_0.gguf --backend cuda \ --audio speech.wav --request-option reference_image_file=portrait.png \ --mode streaming --out-dir outputs/flashhead \ --log --log-file outputs/flashhead/run.log ``` For a cuDNN-enabled source build, add the following option to the command above: ```bash --session-option 'soulx_flashhead.exec_plan={"vae":{"impl":"cudnn"}}' ``` Lite emits 24 RGB24 frames per chunk at 25 FPS. Streaming input is mono 16 kHz; offline input is mixed down and resampled when needed. Default output is 512×512 with four denoising steps. Chunks retain motion continuity from the preceding output. See the [usage and conversion documentation](https://github.com/0xShug0/audio.cpp/blob/main/docs/models/soulx_flashhead.md).