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LatestMotif Technologies2B
Motif TechnologiesText → Video

Motif Releases 2B Open-Source Text-to-Video Model

The new Apache 2.0 licensed model uses a diffusion transformer architecture to offer a new open alternative for video generation research.

Apr 14, 2026
NotableApache 2.0
Motif-Video-2B

Motif Technologies has entered the open-source video generation space with the release of Motif-Video-2B, a new 2-billion-parameter model. Available under a permissive Apache 2.0 license, it provides a new, accessible tool for creating short video clips from both text and image prompts.

The model is built on a diffusion transformer architecture, an approach that has gained significant traction in generative AI for its strong performance in modeling complex data. Unlike many high-profile video systems that remain proprietary, Motif has made the model weights and code publicly available through its Hugging Face repository.

Why it matters

The release of Motif-Video-2B contributes to a growing but still-nascent ecosystem of open-source video generation models. Its relatively modest 2B parameter size makes it more approachable for researchers and developers who may not have access to the massive computational resources required by state-of-the-art commercial systems. By providing a transparent and modifiable foundation, the model can help accelerate experimentation and innovation in the broader community.

Sources

  • Motif-Technologies/Motif-Video-2B

    Hugging Face

    Visit
OlderMoonshot AI Releases Kimi-K2.6 Multimodal ModelMoonshot AI · Vision-Language · 7 months agoNewerQwen Releases 35B Multimodal Mixture-of-Experts ModelQwen · Alibaba · Vision-Language · 7 months ago

Get the model

Hugging Face

Specs

Parameters2B
Resolution720p
Size8.2 GB
PrecisionFP32
ArchitectureMotifVideoPipeline
LicenseAPACHE-2.0
Downloads247
Likes119

Can you run it?

Runs on just about anything.

  • FP32 (as published)

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    9.2 GB
  • 16-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    5.1 GB
  • FP8

    Any modern laptop · 8 GB RAM

    3 GB
Your machine
  • Covers the published checkpoint; text encoders and VAE loaded alongside may add a few GB (many runtimes offload them to CPU).

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Image → VideoText → Video

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