Last updated 06-28-2026
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Unsloth
Unsloth is an open-source stack for training, running, and exporting large language models on your own hardware. It pairs a Python fine-tuning library with Unsloth Studio, a local web UI where you can chat with GGUF and safetensor models, build datasets from documents, and ship trained weights to tools like Ollama or vLLM. The project targets ML engineers, researchers, and hobbyists who want faster LoRA training without giving up model choice.
The core library rewrites training kernels in Triton and claims roughly 2x faster fine-tuning with about 70% less VRAM than standard setups, with support for 500+ text, vision, audio, and embedding models. Unsloth Studio adds no-code workflows: Data Recipes turn PDFs, CSVs, and JSON into training data, while real-time observability tracks loss and GPU use during runs.
You can run everything offline on Mac, Windows, or Linux. Studio includes self-healing tool calling, Bash and Python code execution, web search inside model traces, and an OpenAI-compatible API endpoint for tools like Claude Code or Codex. The open-source package stays on Apache 2.0; Studio UI components use AGPL-3.0.
Train 500+ text, vision, audio, and embedding models with custom Triton kernels
Unsloth Studio runs GGUF and safetensor models 100% offline on Mac and Windows
Data Recipes build training datasets from PDF, CSV, JSON, DOCX, and TXT files
Self-healing tool calling with Bash, Python execution, and web search in chat
Export fine-tuned weights to GGUF, safetensors, Ollama, vLLM, or LM Studio
OpenAI-compatible API endpoint for Claude Code, Codex, and other integrations
Open-source core library with 67,000+ GitHub stars and active community channels.
Claims 2x faster fine-tuning with about 70% less VRAM than standard training stacks.
Unsloth Studio bundles local inference, no-code training, and export in one offline UI.
Supports 500+ model families including text, vision, TTS, and embedding models.
Pro and Enterprise tiers require contacting sales with no public pricing listed.
AMD Studio training support is not available yet despite chat working today.
Studio is still in beta with ongoing fixes and feature rollouts expected.
Is Unsloth free to use?
Yes. Unsloth offers a free open-source version on GitHub with support for Mistral, Gemma, and Llama models, plus 4-bit and 16-bit LoRA fine-tuning. Unsloth Pro and Enterprise tiers with faster multi-GPU training require contacting the team for pricing.
What platforms does Unsloth Studio support?
Unsloth Studio runs locally on Mac, Windows, Linux, and WSL. Training works on NVIDIA RTX 30/40/50, Blackwell, DGX Spark/Station, and Intel GPUs. Mac supports training, MLX, and GGUF inference. AMD chat works today; full Studio training support is listed as coming soon.
Does Unsloth collect user data?
Unsloth states it does not collect usage telemetry. Unsloth Studio runs fully offline and locally. The company only collects minimal hardware information such as GPU type for compatibility checks.
Can I use Unsloth without fine-tuning a model?
Yes. You can download and run any GGUF or supported model in Unsloth Studio without training. The UI also supports chatting, comparing models side by side, and exporting existing weights.
Does Unsloth support an OpenAI-compatible API?
Yes. Unsloth Studio exposes an OpenAI-compatible API endpoint so tools like Claude Code and Codex can call local Qwen, Gemma, and other models with Unsloth inference features such as tool calling and web search.
What license does Unsloth use?
Unsloth uses dual licensing. The core Unsloth package remains Apache 2.0, while optional components including the Unsloth Studio UI are licensed under AGPL-3.0.