---
title: "Tunix"
description: "1 posts about Tunix, summarised, each linking to the original."
---

# Tunix
> 1 posts about Tunix, summarised, each linking to the original.

## Articles

### [Autonomous LLM post-training with Tunix on TPUs](https://yomu.fyi/post/autonomous-llm-post-training-with-tunix-on-tpus.md)
- Company: [Google](https://yomu.fyi/company/google.md)
- Author: Wei Wei
- Published: Sep 11, 2026
- Type: Benchmark

autofinetune applies autonomous research loops to LLM post-training, covering supervised fine-tuning (SFT) and reinforcement learning with GRPO through Tunix, Gemma, Cloud TPUs, Antigravity CLI, and Gemini Flash 3.7. A human defines the arena in program.md and supplies a self-contained run.py, while an agent edits hyperparameters, launches jobs, evaluates a target metric, keeps winning Git commits, reverts regressions, and logs results in results.tsv. On FunctionGemma 270M with google/mobile-actions, 20 Cloud TPU v5e-1 experiments tested LoRA settings, optimization choices, schedules, batch size, and seeds without changing the dataset, epochs, or architecture. A second study used Gemma 3 1B, GSM8K, and Cloud TPU v6e-1 for 40 GRPO experiments over two to three days, improving the combined numerical-and-format reward by about 10%.