Instructions to use FastVideo/FastH3-Omni-Comfy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusion Single File
How to use FastVideo/FastH3-Omni-Comfy with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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license: other
license_name: minimax-h3-community-license-agreement
license_link: https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE
base_model: FastVideo/FastVideo-FastH3-Omni-8-Step-V1
library_name: diffusion-single-file
tags:
- comfyui
- diffusion-single-file
- minimax-h3
- fasth3-omni
- reference-to-video
---
# FastH3 Omni for ComfyUI
ComfyUI-ready BF16 and INT8 ConvRot diffusion models for the final FastH3 Omni release. Generate video and synchronized audio from a prompt and ordered image, video and audio references.
[Release collection](https://huggingface.co/collections/FastVideo/fasth3-omniref) Β· [BF16 release](https://huggingface.co/FastVideo/FastVideo-FastH3-Omni-8-Step-V1) Β· [ComfyUI](https://github.com/Comfy-Org/ComfyUI)
## Install the model files
Choose one diffusion model and place it in `ComfyUI/models/diffusion_models/`:
| File in this repository | Format |
| --- | --- |
| `diffusion_models/fasth3_omniref_8step_pruned_bf16.safetensors` | BF16 diffusion model |
| `diffusion_models/fasth3_omniref_8step_pruned_int8_convrot.safetensors` | INT8 ConvRot diffusion model |
Install one text encoder and one video VAE, plus the audio VAE:
```text
ComfyUI/models/
βββ text_encoders/
β βββ qwen3vl_32b_minimax_h3_bf16.safetensors
β βββ qwen3vl_32b_minimax_h3_int8_convrot.safetensors
β βββ qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
βββ vae/
βββ minimax_h3_audio_vae_fp32.safetensors
βββ minimax_h3_video_vae_fp16.safetensors
βββ minimax_h3_video_vae_int8_convrot.safetensors
```
These files are available in this repository's `text_encoders/` and `vae/` folders. The text encoders include the vision tower needed for references. Accelerated NVFP4 text encoding requires Blackwell hardware; choose BF16 or INT8 for other devices.
For additional diffusion formats, see [FP8 ComfyUI](https://huggingface.co/FastVideo/FastH3-OmniRef-FP8-Comfy) and [NVFP4 QAD ComfyUI](https://huggingface.co/FastVideo/FastH3-OmniRef-NVFP4-QAD-Comfy).
## Generate video and audio
Use a current [ComfyUI](https://github.com/Comfy-Org/ComfyUI) build with native MiniMax-H3 support and the **MiniMax H3 Reference to Video** conditioning node. Supply matching text-encoder, video-VAE and audio-VAE components.
- Eight sampling steps, guidance 1.0.
- Video shift 12.0 and audio shift 3.0.
- Reference inputs use `<Picture 1>`, `<Video 1>` and `<Audio 1>` tags in the prompt.
- The audio VAE is required for synchronized audio output.
ComfyUI uses its own model layout, sampler and runtime kernels; outputs can differ from FastVideo and UniServe.
## Other runtimes
- **UniServe β GB200/B200, RTX PRO 6000 Blackwell and Hopper:** use the [BF16 release](https://huggingface.co/FastVideo/FastVideo-FastH3-Omni-8-Step-V1) and [deployment guide](https://github.com/hao-ai-lab/uniserve/blob/main/docs/minimax_h3/minimax_h3.md).
- **FastVideo local AI β DGX Spark and RTX 5090:** use the [FastVideo-format NVFP4 QAD model](https://huggingface.co/FastVideo/FastH3-OmniRef-NVFP4-QAD) and [local inference guide](https://github.com/hao-ai-lab/FastVideo/blob/main/docs/inference/fasth3_omniref.md).
## Local AI resources
Run FastH3 Omni on **DGX Spark or RTX 5090 through FastVideo** using the [FastVideo-format NVFP4 QAD weights](https://huggingface.co/FastVideo/FastH3-OmniRef-NVFP4-QAD). Start with the [FastVideo cookbook](https://haoailab.com/FastVideo/cookbook/) and [FastH3 Omni recipe builder](https://haoailab.com/FastVideo/cookbook/minimax-h3/fasth3-omniref/); use the [Spark recipe](https://github.com/hao-ai-lab/FastVideo/blob/main/examples/inference/basic/basic_fasth3_omniref_spark.yaml) or [RTX 5090 recipe](https://github.com/hao-ai-lab/FastVideo/blob/main/examples/inference/basic/basic_fasth3_omniref_rtx5090.yaml) and the [local inference guide](https://github.com/hao-ai-lab/FastVideo/blob/main/docs/inference/fasth3_omniref.md) for the AdaLN table, offload and decoder setup.
[FP8 weights](https://huggingface.co/FastVideo/FastH3-OmniRef-FP8) are a separate FastVideo variant; the [FP8 recipe for RTX 4090](https://github.com/hao-ai-lab/FastVideo/blob/main/examples/inference/basic/basic_fasth3_omniref_rtx4090.yaml) illustrates the non-FP4 path with layerwise offload and compatible BF16 encoder components. Use each runtime's matching checkpoint format.
## Acknowledgements
FastH3 Omni was built in close collaboration with [Nuva Lab](https://nuvalab.ai/fasth3/), which co-developed the model with FastVideo, defined and curated the omni reference dataset, and brought production-grounded creative video workflows to FastH3. For dedicated production deployment, fine-tuning on your own data and a creative agent on top, see [Nuva Lab's FastH3-Omni page](https://nuvalab.ai/fasth3/).
Thanks also to the NVIDIA FastGen team.
## License
Use of these weights is governed by the [MiniMax-H3 Community License Agreement](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE).
Bundled ComfyUI tooling retains its own licenses in `conversion/upstream/`.
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