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6 changes: 3 additions & 3 deletions README.md
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Expand Up @@ -32,18 +32,18 @@ Check out our [Read The Docs site](https://maxtext.readthedocs.io/en/latest/) or

## Installation

See our installation guide to [install MaxText with pip](https://maxtext.readthedocs.io/en/latest/guides/install_maxtext.html).
See our installation guide to [install MaxText with pip](https://maxtext.readthedocs.io/en/latest/install_maxtext.html).

## Decoupled mode
See our guide on running MaxText in decoupled mode, without any GCP dependencies in [Decoupled Mode Guide](https://maxtext.readthedocs.io/en/latest/guides/run_maxtext/decoupled_mode.html).
See our guide on running MaxText in decoupled mode, without any GCP dependencies in [Decoupled Mode Guide](https://maxtext.readthedocs.io/en/latest/run_maxtext/decoupled_mode.html).

<!-- NEWS START -->

## 🔥 Latest news 🔥

* \[September 26, 2025\] Vocabulary tiling ([PR](https://github.com/AI-Hypercomputer/maxtext/pull/2242)) is now supported in MaxText! Adjust config `num_vocab_tiling` to unlock more efficient memory usage.
* \[September 24, 2025\] The GPT-OSS family of models (20B, 120B) is now supported.
* \[September 15, 2025\] MaxText is now available as a [PyPI package](https://pypi.org/project/maxtext). Users can now [install maxtext through pip](https://maxtext.readthedocs.io/en/latest/guides/install_maxtext.html).
* \[September 15, 2025\] MaxText is now available as a [PyPI package](https://pypi.org/project/maxtext). Users can now [install maxtext through pip](https://maxtext.readthedocs.io/en/latest/install_maxtext.html).
* \[September 5, 2025\] MaxText has moved to an `src` layout as part of [RESTRUCTURE.md](https://github.com/AI-Hypercomputer/maxtext/blob/aca5b24931ebcbadb55a82e56ebffe8024874028/RESTRUCTURE.md). For existing environments, please run `pip install -e .` from MaxText root.
* \[August 13, 2025\] The Qwen3 2507 MoE family of models is now supported: MoEs: 235B Thinking & 280B Coder as well as existing dense models: 0.6B, 4B, 8B, 14B, and 32B.
* \[July 27, 2025\] Updated TFLOPS/s calculation ([PR](https://github.com/AI-Hypercomputer/maxtext/pull/1988)) to account for causal attention, dividing the attention flops in half. Accounted for sliding window and chunked attention reduced attention flops in [PR](https://github.com/AI-Hypercomputer/maxtext/pull/2009) and [PR](https://github.com/AI-Hypercomputer/maxtext/pull/2030). Changes impact large sequence configs, as explained in this [doc](https://maxtext.readthedocs.io/en/latest/explanations/performance_metrics.html)
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