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unsloth

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Unsloth is the first desktop app to run and train AI models locally. It supports a wide range of models including Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4, and FLUX. Unlike most local model tools that focus only on inference, Unsloth adds a full training stack: fine-tune LLMs, diffusion, TTS, and embedding models 2× faster with 70% less VRAM. It also supports LoRA, QLoRA, RL, GRPO, DPO, and FP8. The app includes built-in Agents & Tools integration (Claude Code, Codex, MCP), private search and RAG, image/video diffusion, and audio support. With hardware support for CPU, NVIDIA, AMD, Intel, macOS, and multi-GPU setups, plus remote access via Cloudflare, Unsloth is a comprehensive local AI studio. It can export to GGUF, NVFP4, FP8 and offers an OpenAI-compatible API for easy deployment.

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Download Download Version

v0.1.701-beta · 44.4 MB

A free, open-source desktop app to run and train LLMs and diffusion models locally, with up to 2× faster fine-tuning and 70% less VRAM.

Core Features

  • Run and train LLMs, diffusion models, audio, embedding, and more
  • 2× faster fine-tuning with 70% less VRAM compared to conventional methods
  • Supports LoRA, QLoRA, full fine-tuning, RL, GRPO, DPO, and FP8
  • Works with agents like Claude Code and Codex, plus private search and RAG
  • Hardware support for CPU, NVIDIA, AMD, Intel, macOS, and multi-GPU

What It Can't Do

  • Even with fast fine-tuning, large training tasks still need sufficient RAM and VRAM; check hardware requirements first
  • First launch may require downloading model files, so ensure a stable internet connection
  • The Vulkan backend only accelerates GGUF inference, not training; training still requires a PyTorch or MLX backend

Use Cases

  • Fine-tune open-source models (e.g., Qwen, DeepSeek, Llama) locally for custom tasks
  • Run a local model hub with agent integration, private knowledge base, and offline inference

Detailed Introduction

Unsloth is the first desktop app to run and train AI models locally. It supports a wide range of models including Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4, and FLUX. Unlike most local model tools that focus only on inference, Unsloth adds a full training stack: fine-tune LLMs, diffusion, TTS, and embedding models 2× faster with 70% less VRAM. It also supports LoRA, QLoRA, RL, GRPO, DPO, and FP8. The app includes built-in Agents & Tools integration (Claude Code, Codex, MCP), private search and RAG, image/video diffusion, and audio support. With hardware support for CPU, NVIDIA, AMD, Intel, macOS, and multi-GPU setups, plus remote access via Cloudflare, Unsloth is a comprehensive local AI studio. It can export to GGUF, NVFP4, FP8 and offers an OpenAI-compatible API for easy deployment.

Tags

LLMfine-tuninglocal AIdeep learningdesktop app

Getting Started

1

Download installer

Click the button above to download the installer for your system

2

Install the software

Install the appropriate package for your distro (dpkg / rpm / AppImage)

3

Download the installer for your operating system (Windows/macOS/Linux)

4

Double-click the installer and follow the setup wizard

5

Launch the Unsloth desktop app, select or download a model, and start using it

Install Guide
  1. Download the installer for your operating system (Windows/macOS/Linux)
  2. Double-click the installer and follow the setup wizard
  3. Launch the Unsloth desktop app, select or download a model, and start using it
File Integrity

SHA-256 checksum verified

Checksum extracted from GitHub official Release page

SHA256 Checksum

3f9fe4489d724d746909e082693a067f6b7e7803d99c5c95efe1ff604edf88e5

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Open Source Transparency

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Environment Guide

Uninstall Info

On Windows, use Settings > Apps to uninstall; on macOS, drag the app to the Trash; on Linux, use your package manager (e.g., apt remove unsloth).

No Extra Dependencies

Ready to use after download. No additional runtime required.

Project Info
LicenseApache-2.0
Last Updated2026-08-14T04:56:59Z
GitHub RepositoryOfficial Website

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