Instructions to use FreeVideoX/Prism-FreeVideo-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FreeVideoX/Prism-FreeVideo-Preview with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FreeVideoX/Prism-FreeVideo-Preview", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Wan2.2
How to use FreeVideoX/Prism-FreeVideo-Preview with Wan2.2:
# 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
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image, export_to_video
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("FreeVideoX/Prism-FreeVideo-Preview", dtype=torch.bfloat16, device_map="cuda")
pipe.to("cuda")
prompt = "A man with short gray hair plays a red electric guitar."
image = load_image(
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
)
output = pipe(image=image, prompt=prompt).frames[0]
export_to_video(output, "output.mp4")Prism for FreeVideo (preview)
English · 中文
Prepared weights of Prism (Tencent, MIT) for the Prism preview in FreeVideo. Prism animates a first frame into a 1280 × 720, 8.5-second video with matching sound (speech, sound effects and music). These files are laid out for FreeVideo's block-streaming engine, which runs Prism on a single NVIDIA RTX 30, 40 or 50 series GPU with 12 GiB of VRAM or more. FreeVideo downloads them for you when you select Prism during setup; you do not need to fetch them by hand.
Contents
| Folder | Size | Used by |
|---|---|---|
int8/ |
46.6 GiB | Every quality level. W8A8 INT8 Prism weights (128-wide Hadamard rotation, quantized from the original weights), the LightX2V Wan2.2-I2V 260412 distillation as an unmerged rank-256 LoRA for the Light level, the UMT5-XXL text encoder (bf16), the Wan2.1 VAE and the DAC audio decoder. |
bf16/ |
60.8 GiB | Optional, the Max level only: the original bf16 Prism weights. It reads the text encoder, tokenizer and VAEs from int8/. |
Each folder has a manifest.json with the size and SHA-256 of every file. Files are split per transformer block (expert_high/blocks/NN.safetensors, expert_low/…, audio/…, bridge/…) so that blocks that do not fit in VRAM can stream from RAM or disk.
Source: FrancisRing/Prism revision 347659c562dcc392c45dfe1673c051e7c62f57ac (preview_alpha), MOVA-360p, and the LightX2V 260412 distillation (rank-256 extraction by Kijai).
Quality levels in FreeVideo
| Level | Recipe | Time on one H200 |
|---|---|---|
| Light | 8 distilled steps; the audio follows the original model's features | about 6 min |
| Medium | 20 steps, original weights, CFG 5 | 15.5 min |
| High | 30 steps, original weights, CFG 5 | 23 min |
| Max | Prism's official 50-step recipe, bf16 weights and exact attention | 62.5 min |
See the FreeVideo Prism guide for the accelerations, the measured quality against the official sampler, and times under smaller VRAM and RAM.
Licenses
Prism weights and code: MIT, Copyright (C) 2026 Tencent. MOVA, Wan2.1 / Wan2.2 (including the UMT5-XXL text encoder and the Wan VAE) and the LightX2V distillation: Apache-2.0. Descript Audio Codec: MIT. These prepared weights are a derivative of those works and keep their licenses; see LICENSE.
中文
Prism(腾讯,MIT 许可证)为 FreeVideo Prism 预览版准备的权重。Prism 可以从一张首帧生成 1280 × 720、8.5 秒、带同步声音(人声、音效、音乐)的视频。文件按 FreeVideo 的分块流式加载引擎排列,可在 12 GiB 显存及以上的 NVIDIA RTX 30/40/50 系单卡上运行。安装 FreeVideo 时勾选 Prism 会自动下载,无需手动获取。
int8/(46.6 GiB):所有档位共用。W8A8 INT8 权重(128 维 Hadamard 旋转,从原版权重量化),轻量档使用的 LightX2V Wan2.2-I2V 260412 蒸馏(未合并的秩 256 LoRA),UMT5-XXL 文本编码器(bf16),Wan2.1 VAE 和 DAC 音频解码器。bf16/(60.8 GiB):可选,仅极致档使用的原版 bf16 权重;文本编码器、分词器和 VAE 读取int8/中的文件。
四个档位:轻量(蒸馏 8 步,H200 约 6 分钟)、标准(原版权重 20 步,15.5 分钟)、精细(30 步,23 分钟)、极致(官方 50 步,bf16 加精确注意力,62.5 分钟)。
许可证:Prism 权重与代码为 MIT(腾讯);MOVA、Wan2.1/Wan2.2(含 UMT5-XXL 文本编码器与 Wan VAE)和 LightX2V 蒸馏模型为 Apache-2.0;Descript Audio Codec 为 MIT。详见 LICENSE。
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Model tree for FreeVideoX/Prism-FreeVideo-Preview
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FrancisRing/Prism