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Fine-tuningUnsloth AI

Unsloth

Fine-tune open LLMs faster with far less VRAM.

Category
Fine-tuning
Pricing
FREEMIUM
Source
Open core
Hosting
Local
Platforms
CLILinuxWindowsmacOS
Models
Multi-model
Verified
Jun 6, 2026

An open-source (Apache-2.0) framework for fine-tuning and running open-weight models with custom CUDA kernels — roughly 2x faster training and large VRAM savings, so 7B–13B models fit on a single consumer GPU. Free tier runs on Colab/Kaggle or locally; Pro and Enterprise tiers add multi-GPU and multi-node speedups. Exports to GGUF/Safetensors for llama.cpp, vLLM, and Ollama.

Capabilities 2

What it actually does — grouped by capability family.

  • Fine-tuning / training (primary capability)
  • Model inference / serving (secondary capability)

Pros & cons

  • LoRA, QLoRA, and full fine-tuning
  • Supports Llama, Qwen, Gemma, DeepSeek
  • Custom CUDA kernels under the hood
  • Exports GGUF/Safetensors for llama.cpp/vLLM/Ollama
  • Runs free on Colab/Kaggle
  • Multi-GPU speedups are paid tiers
  • NVIDIA-centric, CUDA-focused
  • Supports a curated model set
  • Requires ML fine-tuning know-how

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