Unsloth AI
Open-source tool for fast LLM fine-tuning with less memory.
Updated May 2026
Overview
- Website
- unsloth.ai
- Founded
- 2023
- Headquarters
- San Francisco, California, United States
- Ownership
- Private
- Segment
- MLOps & Experiment Tracking
Product overview
Unsloth AI, founded by brothers Daniel and Michael Han, provides open-source tools for reinforcement learning and fine-tuning large language models up to 30x faster with 90% less memory. Their no-code web UI enables local training, running, and exporting of models with auto-dataset creation from various documents. With over 10M monthly downloads and YC backing, they aim to democratize AI development.
Revenue model
Estimated $1M annual revenue; $500K total funding
Moat
- Proprietary Technology
- Cost Advantages
- Scale Advantages
Unsloth AI's primary competitive moat is its proprietary technology enabling 2-5x faster LLM fine-tuning and 70% less VRAM usage on consumer hardware, including breakthroughs like GRPO training and Dynamic 2.0 quantization that outperform rivals on benchmarks such as 5-shot MMLU and Aider Polyglot. This provides significant cost and speed advantages, fast iteration for users, and broad model coverage, distinguishing it from competitors like Axolotl and TorchTune.
Headwinds
Open-source model makes monetization challenging as competitors can freely use and modify their core technology.