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unslothai/unsloth

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•로컬 모델 실행·학습용 도구 → LLM과 diffusion 모델 등을 데스크톱 UI에서 활용

•추론 전용 도구와 달리 실행과 학습을 함께 제공하고 여러 운영체제·하드웨어 지원을 내세우는 포지션

•모델·하드웨어별 학습 지원 범위와 메모리 요구량 확인 필요, 나열된 모든 조합의 동등한 지원 여부 검증 필요

Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4, FLUX and more.

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출처: github.com
피드: GitHub 활발
수집/분석 기준: 2026. 9. 8. 오전 9:00
원문 확인: 원문 열기

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Unsloth is the first desktop app to run and train models.

Features •

Quickstart •

Notebooks •

Documentation

## ⚡ Get started

Download the native Unsloth Desktop app for your operating system:

Platform

Link

Windows

Download

macOS

Download

Linux / Ubuntu (deb)

Download

Linux (AppImage)

Download

Download from [Unsloth](https://unsloth.ai/download) or [GitHub Releases](https://github.com/unslothai/unsloth/releases).

Or if you prefer to install manually:

#### macOS, Linux, WSL:

curl -fsSL https://unsloth.ai/install.sh | sh

#### Windows:

irm https://unsloth.ai/install.ps1 | iex

#### Community:

•[Discord](https://discord.gg/unsloth)

•[𝕏 (Twitter)](https://x.com/UnslothAI)

•[Reddit](https://reddit.com/r/unsloth)

## ⭐ Features

Unsloth works on Windows, Linux, WSL and macOS. We support Multi GPU setups, NVIDIA, AMD, Intel GPUs, CPUs and the Vulkan backend.

### Run & Build with AI

•Run and train LLMs, MLX, GGUF, diffusion, embedding, audio models: [Qwen3.8](https://unsloth.ai/docs/models/qwen3.8), [GLM-5.3-Flash](https://unsloth.ai/docs/models/glm-5.3-flash), [Kimi K3](https://unsloth.ai/docs/models/kimi-k3), MiniMax-H3, [DeepSeek-V4](https://unsloth.ai/docs/models/deepseek-v4), [Gemma 4](https://unsloth.ai/docs/models/gemma-4).

•Agents & Tools: Use local models with [Claude Code](https://unsloth.ai/docs/basics/claude-code), [Codex](https://unsloth.ai/docs/basics/codex), and [MCP](https://unsloth.ai/docs/basics/mcp), including tool calling and code execution.

•Search & RAG: Use private and unlimited web search, deep research, auto-compaction (rolling context window) and RAG.

•Image and video: Run and train [image](https://unsloth.ai/docs/basics/diffusion-image) and video diffusion or multimodal models

•Remote & LAN: Access your local models from any device on [LAN](https://unsloth.ai/docs/basics/lan) or remotely through secure [Cloudflare](https://unsloth.ai/docs/basics/how-to-serve-local-llms-anywhere-secure-remote-access-with-cloudflare-and-unsloth) HTTPS.

•Connect: Serve models through an [OpenAI compatible API](https://unsloth.ai/docs/basics/api). Also connect your ChatGPT/Codex subscription and [cloud providers](https://unsloth.ai/docs/integrations/connections)

### Train & Deploy

•Fine-tuning: Train LLMs, diffusion, TTS, and embedding models 2× faster with 70% less VRAM with [no accuracy loss](https://unsloth.ai/blog#training)

•Complete support: Supports [reinforcement learning](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide), LoRA, QLoRA, full fine tuning, pretraining, RL, GRPO, DPO, and FP8.

•Export & Deploy: [Export](https://unsloth.ai/docs/new/studio/export) or Deploy models with including [GGUF](https://unsloth.ai/docs/basics/inference-and-deployment/saving-to-gguf), NVFP4, FP8 and more formats.

•Datasets: Build datasets from PDFs, CSVs, DOCX files, and more with [Data Recipes](https://unsloth.ai/docs/new/studio/data-recipe).

## 🚀 Unsloth Start

[Unsloth Start](https://unsloth.ai/docs/integrations/unsloth-start) connects [Claude Code](https://unsloth.ai/docs/basics/claude-code), [Codex](https://unsloth.ai/docs/basics/codex) and other agents to local models with one command.

unsloth start claude --model unsloth/Qwen3.8-27B-GGUF:UD-Q4_K_XL

Agent	Command
Claude Code	`unsloth start claude`
OpenAI Codex	`unsloth start codex`
Hermes Agent	`unsloth start hermes`
OpenClaw	`unsloth start openclaw`
OpenCode	`unsloth start opencode`
DeepSeek Harness	`unsloth start dsh`

## 📥 Install

Unsloth can be used in three ways: [Unsloth Desktop](https://unsloth.ai/download), the desktop app; [Unsloth Studio](https://unsloth.ai/docs/new/studio/), the web UI; or Unsloth Core, the code based version.

### Unsloth Desktop (recommended)

Platform

Link

Windows

Download

macOS

Download

Linux / Ubuntu (deb)

Download

Linux (AppImage)

Download

### Unsloth Studio (web UI)

#### macOS, Linux, WSL:

curl -fsSL https://unsloth.ai/install.sh | sh

#### Windows:

irm https://unsloth.ai/install.ps1 | iex

#### Launch

unsloth studio

#### HTTP Secure Deployment

unsloth studio --secure

#### Docker

Use our [Docker image](https://hub.docker.com/r/unsloth/unsloth) ``unsloth/unsloth. On Linux, set up GPU access once with curl -fsSL https://raw.githubusercontent.com/unslothai/unsloth/main/docker/install_nvidia_toolkit.sh -o install_nvidia_toolkit.sh && sudo -E bash install_nvidia_toolkit.sh` (Windows: Docker Desktop with WSL 2). Run:

docker run -d --gpus all --ipc=host \
  -p 8000:8000 -p 8888:8888 \
  -e UNSLOTH_STUDIO_PASSWORD="mypassword" -e JUPYTER_PASSWORD="mypassword" \
  -v "$PWD":/workspace/host \
  unsloth/unsloth

unslothai/unsloth

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