main-database/Cosmos.yaml at preview · Language-Technology-Assessment/main-database · GitHub

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---
# Thank you for contributing!
# In filling out this yaml file, please follow the criteria as described here:
# https://osai-index.eu/contribute

# You're free to build on this work and reuse the data. It is licensed under CC-BY 4.0, with the
# stipulation that attribution should come in the form of a link to https://osai-index.eu/
# and a citation to the peer-reviewed paper in which the dataset & criteria were published:

# Liesenfeld, A. and Dingemanse, M., 2024. Rethinking open source generative AI: open-washing and the EU AI Act. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 1774-1787).

# Organization tags:
# - National origin: United States
# - Contributor type: Non-academic (Company)

# Training compute:
# - Base model training compute: unknown
# - End model training compute: unknown

system:
    name: Cosmos
    link: https://huggingface.co/nvidia/Cosmos-Predict2.5-2B
    type: video
    performanceclass: full
    basemodelname: Cosmos-Predict2.5-14B-Pre-trained
    endmodelname: Cosmos-Predict2.5-14B-Post-trained
    endmodellicense: NVIDIA Open Model License
    releasedate: 2025-10
    notes: Given a text or video input, predicts the next five seconds.

org:
    name: NVIDIA
    link: https://www.nvidia.com
    notes: NVIDIA, a major chip manufacturer.

# availability:
datasources_basemodel:
    class: closed
    link: https://arxiv.org/pdf/2511.00062
    notes: Preprint only provides high-level description.

datasources_endmodel:
    class: closed
    link: https://arxiv.org/pdf/2511.00062
    notes: Preprint only provides high-level description.

weights_basemodel:
    class: open
    link: https://huggingface.co/nvidia/Cosmos-Predict2.5-14B
    notes: Weights available on HuggingFace.

weights_endmodel:
    class: open
    link: https://huggingface.co/nvidia/Cosmos-Predict2.5-14B
    notes: Weights available on HuggingFace.

trainingcode:
    class: open
    link: https://github.com/nvidia-cosmos/cosmos-predict2.5
    notes: Repository exists with training script.

# documentation:
code:
    class: open
    link: https://github.com/nvidia-cosmos/cosmos-predict2.5
    notes: Repository is well-documented.

hardware_architecture:
    class: open
    link: https://arxiv.org/pdf/2511.00062
    notes: Hardware architecture outlined in preprint.

preprint:
    class: open
    link: https://arxiv.org/pdf/2511.00062
    notes: preprint published on arXiv.

paper:
    class: closed
    link:
    notes: No peer-reviewed publication found.

modelcard:
    class: open
    link: https://huggingface.co/nvidia/Cosmos-Predict2.5-14B
    notes: Model card contains requisite information.

datasheet:
    class: closed
    link:
    notes: No datasheet found.

# access:
licenses:
    class: partial
    link: ["https://huggingface.co/nvidia/Cosmos-Predict2.5-14B", "https://github.com/nvidia-cosmos/cosmos-predict2.5"]
    notes: "Weights: NVIDIA Open Model License. Code: Apache-2.0. Data: not released."