main-database/Minimax.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: China
# - Contributor type: Non-academic (Chinese AI Tiger)

system:
    name: Minimax-M2
    link: https://huggingface.co/MiniMaxAI/MiniMax-M2
    type: text
    performanceclass: latest
    basemodelname: MiniMax-Text-01?
    endmodelname: MiniMax-M2
    endmodellicense: Modified MIT
    releasedate: 2025-10
    notes: SOTA model by Minimax

org:
    name: Minimax AI
    link: https://www.minimaxi.com/en
    notes: Chinese artificial intelligence company.

# availability:
datasources_basemodel:
    class: closed
    link:
    notes: No base model datasources found.

datasources_endmodel:
    class: closed
    link:
    notes: No end model datasources found.

weights_basemodel:
    class: open
    link: https://huggingface.co/MiniMaxAI/MiniMax-Text-01
    notes: Model weights released on HuggingFace.

weights_endmodel:
    class: open
    link: https://huggingface.co/MiniMaxAI/MiniMax-M2
    notes: Model weights released on HuggingFace.

trainingcode:
    class: closed
    link: https://github.com/MiniMax-AI/MiniMax-M2
    notes: Repo exists, however does not contain training code.

# documentation:
code:
    class: closed
    link:
    notes:

hardware_architecture:
    class: partial
    link: https://arxiv.org/pdf/2506.13585
    notes: Architecture described on very high level in paper.

preprint:
    class: open
    link: https://arxiv.org/pdf/2506.13585
    notes: Preprint published on arXiv.

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

modelcard:
    class: closed
    link: https://huggingface.co/MiniMaxAI/MiniMax-M2
    notes: Model primarily contains inference information.

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

# access:
package:
    class: closed
    link:
    notes: No package found.

api:
    class: closed
    link: https://www.minimax.io/platform/document/platform%20introduction?key=66701c8e1d57f38758d58198
    notes: closed API only
    metaprompt: closed

licenses:
    class: closed
    link: https://huggingface.co/MiniMaxAI/MiniMax-M2
    notes: Modified MIT, not an OSI-approved license.