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@ -23,6 +23,7 @@ Notebooks are beginner friendly. Read our [guide](https://docs.unsloth.ai/get-st
| Model | Free Notebooks | Performance | Memory use |
|-----------|---------|--------|----------|
| **gpt-oss (20B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-(20B)-Fine-tuning.ipynb) | 1.5x faster | 70% less |
| **Mistral Ministral 3 (3B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_VL_(3B)_Vision.ipynb) | 1.5x faster | 60% less |
| **gpt-oss (20B): GRPO** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-(20B)-GRPO.ipynb) | 2x faster | 80% less |
| **Qwen3: Advanced GRPO** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_(4B)-GRPO.ipynb) | 2x faster | 50% less |
| **Qwen3-VL (8B): GSPO** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_(8B)-Vision-GRPO.ipynb) | 1.5x faster | 80% less |
@ -31,7 +32,6 @@ Notebooks are beginner friendly. Read our [guide](https://docs.unsloth.ai/get-st
| **DeepSeek-OCR (3B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_(3B).ipynb) | 1.5x faster | 30% less |
| **Llama 3.1 (8B) Alpaca** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-Alpaca.ipynb) | 2x faster | 70% less |
| **Llama 3.2 Conversational** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_(1B_and_3B)-Conversational.ipynb) | 2x faster | 70% less |
| **Qwen3 (14B) Reasoning** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_(14B)-Reasoning-Conversational.ipynb) | 2x faster | 70% less |
| **Orpheus-TTS (3B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Orpheus_(3B)-TTS.ipynb) | 1.5x faster | 50% less |
- See all our notebooks for: [Kaggle](https://github.com/unslothai/notebooks?tab=readme-ov-file#-kaggle-notebooks), [GRPO](https://docs.unsloth.ai/get-started/unsloth-notebooks#grpo-reasoning-rl-notebooks), **[TTS](https://docs.unsloth.ai/get-started/unsloth-notebooks#text-to-speech-tts-notebooks)** & [Vision](https://docs.unsloth.ai/get-started/unsloth-notebooks#vision-multimodal-notebooks)
@ -51,17 +51,19 @@ Use our official [Unsloth Docker image](https://hub.docker.com/r/unsloth/unsloth
For RTX 50x, B200, 6000 GPUs: `pip install unsloth`. Read our [Blackwell Guide](https://docs.unsloth.ai/basics/training-llms-with-blackwell-rtx-50-series-and-unsloth) and [DGX Spark Guide](https://docs.unsloth.ai/new/fine-tuning-llms-with-nvidia-dgx-spark-and-unsloth) for more details.
## 🦥 Unsloth News
- **Ministral 3** by Mistral: Run Ministral 3 or fine-tune with our vision or RL sodoku notebook. [Guide](https://docs.unsloth.ai/new/ministral-3) • [Notebooks](https://docs.unsloth.ai/new/ministral-3#fine-tuningb)
- **500K Context Fine-tuning**: Training a 20B model with >500K token context windows is now possible on a single 80GB GPU. [Blog](https://docs.unsloth.ai/new/500k-context-length-fine-tuning)
- **FP8 Reinforcement Learning**: You can now do FP8 GRPO on consumer GPUs. [Blog](https://docs.unsloth.ai/new/fp8-reinforcement-learning) • [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_8B_FP8_GRPO.ipynb)
- **DeepSeek-OCR**: Fine-tune to improve language understanding by 89%. [Guide](https://docs.unsloth.ai/new/deepseek-ocr-run-and-fine-tune) • [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_(3B).ipynb)
- **Docker**: Use Unsloth with no setup & environment issues with our new image. [Guide](https://docs.unsloth.ai/new/how-to-train-llms-with-unsloth-and-docker) • [Docker image](https://hub.docker.com/r/unsloth/unsloth)
- **gpt-oss RL**: Introducing the fastest possible inference for gpt-oss RL! [Read blog](https://docs.unsloth.ai/new/gpt-oss-reinforcement-learning)
- **Vision RL**: You can now train VLMs with GRPO or GSPO in Unsloth! [Read guide](https://docs.unsloth.ai/new/vision-reinforcement-learning-vlm-rl)
- **Quantization-Aware Training**: We collabed with Pytorch, recovering ~70% accuracy. [Read blog](https://docs.unsloth.ai/new/quantization-aware-training-qat)
- **gpt-oss** by OpenAI: Read our [Unsloth Flex Attention](https://docs.unsloth.ai/new/long-context-gpt-oss-training) blog and [gpt-oss Guide](https://docs.unsloth.ai/basics/gpt-oss). 20B works on 14GB VRAM. 120B on 65GB.
<details>
<summary>Click for more news</summary>
- **Quantization-Aware Training**: We collabed with Pytorch, recovering ~70% accuracy. [Read blog](https://docs.unsloth.ai/new/quantization-aware-training-qat)
- **Memory-efficient RL**: We're introducing even better RL. Our new kernels & algos allows faster RL with 50% less VRAM & 10× more context. [Read blog](https://docs.unsloth.ai/new/memory-efficient-rl)
- **Gemma 3n** by Google: [Read Blog](https://docs.unsloth.ai/basics/gemma-3n-how-to-run-and-fine-tune). We [uploaded GGUFs, 4-bit models](https://huggingface.co/collections/unsloth/gemma-3n-685d3874830e49e1c93f9339).
- **[Text-to-Speech (TTS)](https://docs.unsloth.ai/basics/text-to-speech-tts-fine-tuning)** is now supported, including `sesame/csm-1b` and STT `openai/whisper-large-v3`.