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- New GitHub page for NVIDIA Cosmos: https://github.com/nvidia-cosmos
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-# NVIDIA Cosmos
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-Cosmos World Foundation Models come in three model types which can all be customized in post-training: [cosmos-predict](https://github.com/nvidia-cosmos/cosmos-predict1), [cosmos-transfer](https://github.com/nvidia-cosmos/cosmos-transfer1), and [cosmos-reason](https://github.com/nvidia-cosmos/cosmos-reason1):
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-| | Predict | Transfer | Reason |
-| ----- | :---: | :---: | :---: |
-| **Type** | World Generation | Multi-Controlnet | Reasoning VLM |
-| **Function** | Predict novel future frames given initial frames | Transfer existing control frames into photoreal frames within a video clip | Reason against frames within a video clip |
-| **Use Cases** | Data Generation & Policy Evaluation | Data Augmentation | Data Curation |
-| **Inputs** | Text, Image, Video | Multiple Video Modalities such as RGB, Depth, Segmentation, and more. | Video & Text |
-| **Outputs** | Video | Video | Text |
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-#
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-# Use Cases in Physical AI Development
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-Our world foundation models are purpose-built to accelerate improving performance in downstream model tasks in various stages, as illustrated here in the flywheel.
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-**This repository is no longer maintained and will soon be deprecated.** To view the initial release of NVIDIA Cosmos from this repository, please check out branch `archived-ces2025`.
+**This repository has been deprecated and is no longer maintained.** To view the initial release of NVIDIA Cosmos from this repository, please check out branch `archived-ces2025`.
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