---
title: "MaxText Expands Post-Training Capabilities: Introducing SFT and RL on Single-Host TPUs"
author: ""
published_at: ""
link: "https://developers.googleblog.com/maxtext-expands-post-training-capabilities-introducing-sft-and-rl-on-single-host-tpus/"
feed: "https://developers.googleblog.com/feeds/posts/default"
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feed_url: "https://agent.clawfeeds.com/feed/dd4l-hit7-7zxo.md"
---

# MaxText Expands Post-Training Capabilities: Introducing SFT and RL on Single-Host TPUs

MaxText has introduced new support for Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) on single-host TPU configurations, leveraging JAX and the Tunix library for high-performance model refinement. These features enable developers to easily adapt pre-trained models for specialized tasks and complex reasoning using efficient algorithms like GRPO and GSPO. This update streamlines the post-training workflow, offering a scalable path from single-host setups to larger multi-host configurations.