September-2025-v3

We’re introducing gpt-oss RL support and the fastest RL inference and lowest VRAM use vs. any implementation. Blog: https://docs.unsloth.ai/new/gpt-oss-reinforcement-learning
- Unsloth now offers the fastest inference (~3x faster), lowest VRAM (50% less) and most context (8x longer) for gpt-oss RL vs. any implementation - with no accuracy loss.
- Since RL on gpt-oss isn't yet vLLM compatible, we **rewrote Transformers inference** code to enable faster inference
- gpt-oss-20b GSPO **free** [Colab notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-(20B)-GRPO.ipynb)
- This notebook automatically creates faster matrix multiplication kernels and uses a new Unsloth reward function. We also show how to [counteract reward-hacking](https://docs.unsloth.ai/new/gpt-oss-reinforcement-learning#can-we-counter-reward-hacking) which is one of RL's biggest challenges.

<img width="300" alt="gptoss rl" src="https://github.com/user-attachments/assets/d6ab98ea-590d-433f-94aa-e30f535ebbad" />

- We previously released [**Vision RL**](https://docs.unsloth.ai/new/vision-reinforcement-learning-vlm-rl) with GSPO support
- ⚠️ Reminder to NOT use **Flash Attention 3** for gpt-oss as it'll make your training loss wrong.
- **DeepSeek-V3.1-Terminus** is here and you can run locally via our [GGUF](https://huggingface.co/unsloth/DeepSeek-V3.1-Terminus-GGUF)
Read how our 3-bit GGUF beats Claude-4-Opus (thinking) on Aider Polyglot [here](https://docs.unsloth.ai/new/unsloth-dynamic-ggufs-on-aider-polyglot)
- **Magistral 1.2** is here and you can run it locally [here](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms/magistral-how-to-run-and-fine-tune#tutorial-how-to-run-llama-4-scout-in-llama.cpp) or fine-tune it for free by using our [Kaggle notebook](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms/magistral-how-to-run-and-fine-tune#fine-tuning-magistral-with-unsloth)
- Fine-tuning the new Qwen3 models including **Qwen3-VL**, Qwen3-Omni and **Qwen3-Next** should work in Unsloth if you install the latest transformers. The models are big however so ensure you have enough VRAM.
- **BERT** is now fixed! Feel free to use our [BERT fine-tuning notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/bert_classification.ipynb)

**Don't forget to also join our Reddit: [r/unsloth](https://www.reddit.com/r/unsloth/) 🥰**

## What's Changed
* Bug fixes by @danielhanchen in https://github.com/unslothai/unsloth/pull/3329
* Fix QAT + LoRA fast path, add tests by @andrewor14 in https://github.com/unslothai/unsloth/pull/3307
* Use gemma3n embedder patch + adjust FORCE_FLOAT32 match logic by @mmathew23 in https://github.com/unslothai/unsloth/pull/3332
* Synthetic Data updates by @mmathew23 in https://github.com/unslothai/unsloth/pull/3333
* Fix loading issues for BERT by @Etherll in https://github.com/unslothai/unsloth/pull/3339
* Bug fixes by @danielhanchen in https://github.com/unslothai/unsloth/pull/3335
* peft_config before model_config by @mmathew23 in https://github.com/unslothai/unsloth/pull/3342
* specify different tokenizer_path/name by @mmathew23 in https://github.com/unslothai/unsloth/pull/3343
* correct python support statement by @laz-001 in https://github.com/unslothai/unsloth/pull/3374
* GPT OSS RL by @danielhanchen in https://github.com/unslothai/unsloth/pull/3362

## New Contributors
* @laz-001 made their first contribution in https://github.com/unslothai/unsloth/pull/3374

**Full Changelog**: https://github.com/unslothai/unsloth/compare/September-2025-v2...September-2025-v3