Model reference · open weights

LingBot-Video-Dense

Video FastVideo Text→video 1 build Open weights 0 dl/mo

LingBot-Video-Dense is an open-weight video model from FastVideo. LingBot-Video-Dense-1.3B-Diffusers (BF16) weighs 12.2 GB; the smallest configuration that runs it is RTX 3060 12 GB.

What it is

Released byFastVideo
Released2026-07-13
VRAM12.2 GB for the weights

What it runs on

Memory and cards for LingBot-Video-Dense-1.3B-Diffusers (BF16)

12.2 GBweights, file size
8.9 GBbiggest part
537 MBruntime overhead
CardWeightsMemory
RTX 3060 12 GBfits (encoders offloaded)11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What FastVideo says about LingBot-Video-Dense

This repository contains the released LingBot-Video Dense 1.3B checkpoint in the component layout loaded natively by FastVideo. ## Usage

Use a FastVideo revision containing LingBot-Video support:

from fastvideo import VideoGenerator

generator = VideoGenerator.from_pretrained(
    "FastVideo/LingBot-Video-Dense-1.3B-Diffusers",
    num_gpus=1,
    use_fsdp_inference=False,
    text_encoder_cpu_offload=True,
)
result = generator.generate({
    "prompt": "A red fox runs through fresh snow at sunrise.",
    "output": {"output_path": "outputs/lingbot-video", "save_video": True},
})
generator.shutdown()

The default preset generates 121 frames at 832×480 with 40 denoising steps.

Read the full model card

Provenance

  • Original model: https://huggingface.co/robbyant/lingbot-video-dense-1.3b
  • Original code: https://github.com/robbyant/lingbot-video
  • FastVideo port: https://github.com/hao-ai-lab/FastVideo/pull/1595

The original model and this converted package are distributed under the Apache-2.0 license declared by the released checkpoint.

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

Running it yourself

Run it on a rented GPU

Rent a machine by the hour. How to run this model is on its model card.

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