MaxText
MaxText is a research stack maintained by Google (AI Hypercomputer GitHub organization)245. Its source code is public13 under the Apache License 2.03.
MaxText is an open-source LLM library and reference implementation written in Python and JAX for training on Google Cloud TPUs and GPUs. It provides implementations of Gemma, Llama, DeepSeek, Qwen, Mistral, and other open model architectures, with support for pre-training and for post-training methods such as supervised fine-tuning and reinforcement learning.12
- Repository: GitHub repository (external site: github.com)
- Documentation: Documentation (external site: maxtext.readthedocs.io)
- License: License (external site: github.com)
Availability and license
Overall availability
Documented as available to the general public. Access conditions and license terms may still apply.13
Availability is separate from permission: read the license before using or redistributing.
Component reuse rights
- weights
- Unknown — no complete fact-level rights review
- code
- Unknown — no complete fact-level rights review
- data
- Unknown — no complete fact-level rights review
- documentation
- Unknown — no complete fact-level rights review
No complete system-rights review is recorded for this release.
Public materials checklist
| Item | Status | Notes and evidence |
|---|---|---|
| Source codeIs the source code publicly readable? | Public | Public GitHub repository under the Apache License 2.0.13 |
| DocumentationIs user documentation published? | Public | Documentation is published on Read the Docs.62 |
| Training codeDoes it include code for training models? | Public | Includes code for pre-training and for post-training (supervised fine-tuning and reinforcement learning).2 |
| Data informationAre the data it expects or ships with documented? | Public | The documentation describes the supported data input pipelines (Grain, Hugging Face, and TFDS) and the file formats each accepts.7 |
| ReproducibilityAre instructions for reproducing reported results published? | Unknown | Getting-started and tutorial guides are published; whether they reproduce specific reported performance results was not assessed.2 |
What it is useful for
The README presents MaxText as a starting point to fork for pre-training experiments on TPU or GPU and as a framework for post-training existing models.2
Run and use notes
Organization context
What this catalog does not know
- Reproducibility: unknown.
Have a primary source? How to report a correction.
U.S. eligibility
Eligible · basis: U.S.-governed project
MaxText's source files carry a Google LLC copyright notice, its contribution guide requires Google's Contributor License Agreement and follows Google's Open Source Community Guidelines, and it is hosted in the AI Hypercomputer GitHub organization, which describes itself as covering Google Cloud AI Hypercomputer. Google LLC is a Delaware subsidiary of Alphabet Inc., whose principal executive offices are in Mountain View, California, per its fiscal 2025 Form 10-K.245910
Sources
This listing is not an endorsement, a safety assessment, or a federal approval.
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Cite this page
APA style
USASI. (2026, September 29). MaxText. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/maxtext/
BibTeX
@misc{usasi_maxtext,
author = {{USASI}},
title = {MaxText},
year = {2026},
month = sep,
howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/maxtext/}},
note = {United States of America Superintelligence. Last updated 2026-09-29}
}The date is when this page was last updated. Add the date you read it if your style needs one.
For maintainers: a “Listed in USASI” badge
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