> For the complete documentation index, see [llms.txt](https://unsloth.ai/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://unsloth.ai/docs/docs.md).

# Unsloth Docs

Unsloth lets you run and train AI models on your own local hardware via an open-source UI.

Our docs will guide you through running & training your own LLM locally.

<a href="https://unsloth.ai/download" class="button primary" data-icon="down-to-bracket">Download Unsloth</a><a href="/pages/0M3SoK9xrgfNCqWbWpMu#features" class="button secondary" data-icon="sparkles">Features</a><a href="https://github.com/unslothai/unsloth" class="button secondary" data-icon="github">GitHub</a>

<table data-card-size="large" data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-cover data-type="image">Cover image</th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><h4>Introducing Unsloth Desktop</h4></td><td>The first desktop app to run and train LLMs and diffusion models.</td><td><a href="/files/XZEkfMzpyz0aroG4AkM9">/files/XZEkfMzpyz0aroG4AkM9</a></td><td><a href="/pages/0M3SoK9xrgfNCqWbWpMu">/pages/0M3SoK9xrgfNCqWbWpMu</a></td></tr><tr><td><h4>Qwen3.8-27B is here!</h4></td><td>Run Qwen3.8-27B and Qwen3.8-2.4T in Unsloth!</td><td><a href="/files/T7cO71XRMo56f8iAJlTI">/files/T7cO71XRMo56f8iAJlTI</a></td><td><a href="/pages/CLyZKmpoJZpdaJXhLW4v">/pages/CLyZKmpoJZpdaJXhLW4v</a></td></tr></tbody></table>

<table data-view="cards" data-full-width="false"><thead><tr><th></th><th></th><th data-hidden data-card-cover data-type="image">Cover image</th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Dynamic V3.0 GGUFs</strong></td><td>New Dynamic 3.0 Unsloth quants for Qwen3.8.</td><td><a href="/files/YaMUnC25PdDODQnYULLL">/files/YaMUnC25PdDODQnYULLL</a></td><td><a href="/pages/QznsvWxKKvrY6PdiByzz">/pages/QznsvWxKKvrY6PdiByzz</a></td></tr><tr><td><strong>Meta Muse Glimmer</strong></td><td>The new 30B open model by Meta.</td><td><a href="/files/6Mfar7OZnC0seQ85ClWM">/files/6Mfar7OZnC0seQ85ClWM</a></td><td><a href="/pages/1hXO5DDKxmP1zKUUnBnA">/pages/1hXO5DDKxmP1zKUUnBnA</a></td></tr><tr><td><strong>DeepSeek-V4-Flash-0731</strong></td><td>The new 284B model released on July 31.</td><td><a href="/files/vWDCobEuT1Be0ZMswwnt">/files/vWDCobEuT1Be0ZMswwnt</a></td><td><a href="/pages/2f4eyCpdyRknNuEtv22n">/pages/2f4eyCpdyRknNuEtv22n</a></td></tr></tbody></table>

### ⚡ Quickstart

Unsloth supports MacOS, Linux, [Windows](/docs/get-started/install/windows-installation.md), [NVIDIA](/docs/get-started/install/pip-install.md), [AMD](/docs/get-started/install/amd.md), Intel and CPU setups. See: [Unsloth Requirements](/docs/get-started/fine-tuning-for-beginners/unsloth-requirements.md). Download the native desktop app for your operating system:

<a href="https://unsloth.ai/download" class="button primary" data-icon="down-to-bracket">Download Unsloth Desktop</a>

* <i class="fa-apple">:apple:</i> [Download for macOS](https://unsloth.ai/download/mac)
* <i class="fa-windows">:windows:</i> [Download for Windows](https://unsloth.ai/download/windows)
* <i class="fa-linux">:linux:</i> [Download for Linux](https://unsloth.ai/download/linux)

Or, if you prefer manual installation:

**MacOS, Linux, WSL:**

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

**Windows PowerShell:**

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

{% columns %}
{% column width="50%" %}
{% content-ref url="/pages/BAeSP6aOxvSeDUzCgKOK" %}
[Complete LLM Directory](/docs/models/tutorials.md)
{% endcontent-ref %}

{% content-ref url="/pages/nw2c1elNySGBBav8WP9B" %}
[Fine-tuning Guide](/docs/get-started/fine-tuning-llms-guide.md)
{% endcontent-ref %}
{% endcolumn %}

{% column width="50%" %}
{% content-ref url="/pages/nQlzs5BcvqlaEjhsgbtY" %}
[Models](/docs/get-started/unsloth-model-catalog.md)
{% endcontent-ref %}

{% content-ref url="/pages/7sCtc6YWnJBYthTjQsr7" %}
[Unsloth API](/docs/basics/api.md)
{% endcontent-ref %}
{% endcolumn %}
{% endcolumns %}

Then open `http://127.0.0.1:8888` (or your specific URL) in your browser.

### 👾 Unsloth Start

{% columns %}
{% column width="58.333333333333336%" %}
[Unsloth Start](/docs/integrations/unsloth-start.md) lets you connect [Claude Code](/docs/basics/claude-code.md), [Codex](/docs/basics/codex.md) and other agents to local models via the `unsloth start` command.

Start Unsloth, load a model, open your project folder, and then run:

```bash
unsloth start claude
```

Replace `claude` with any agent below:
{% endcolumn %}

{% column width="41.666666666666664%" %}

<figure><img src="/files/HrMdgp7HDGelphJEpwCG" alt="" width="563"><figcaption><p>Claude Code running with Qwen3.5 locally.</p></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

| Agent                                                              | Command                  |
| ------------------------------------------------------------------ | ------------------------ |
| <i class="fa-claude">:claude:</i> Claude Code                      | `unsloth start claude`   |
| <i class="fa-openai">:openai:</i> OpenAI Codex                     | `unsloth start codex`    |
| <i class="fa-caduceus">:caduceus:</i> Hermes Agent                 | `unsloth start hermes`   |
| <i class="fa-lobster">:lobster:</i> OpenClaw                       | `unsloth start openclaw` |
| <i class="fa-rectangle-vertical">:rectangle-vertical:</i> OpenCode | `unsloth start opencode` |

### 🦥 Why Unsloth?

* We directly collab with teams behind [gpt-oss](https://docs.unsloth.ai/new/gpt-oss-how-to-run-and-fine-tune#unsloth-fixes-for-gpt-oss), [Qwen3](https://www.reddit.com/r/LocalLLaMA/comments/1kaodxu/qwen3_unsloth_dynamic_ggufs_128k_context_bug_fixes/), [Llama 4](https://github.com/ggml-org/llama.cpp/pull/12889), [Mistral](https://huggingface.co/mistralai/Mistral-Medium-3.5-128B/discussions/18), [Gemma 1-3](https://news.ycombinator.com/item?id=39671146) and [Phi-4](https://unsloth.ai/blog/phi4), where we’ve **fixed critical bugs** that greatly improved model accuracy. Andrej Karpathy for example has [praised our work](https://x.com/karpathy/status/1765473722985771335).
* Unsloth streamlines local training, inference, data, and deployment
* Unsloth supports inference and training for 500+ models: [vision](/docs/basics/vision-fine-tuning.md), [TTS](/docs/basics/text-to-speech-tts-fine-tuning.md), [embedding](/docs/basics/embedding-finetuning.md), [RL](/docs/get-started/reinforcement-learning-rl-guide.md)

### ⭐ Features

Unsloth lets you run and train models for text, [audio](https://unsloth.ai/docs/basics/text-to-speech-tts-fine-tuning), [embedding](https://unsloth.ai/docs/new/embedding-finetuning), [vision](https://unsloth.ai/docs/basics/vision-fine-tuning) and more. Unsloth provides many key features for both inference and training:

#### Inference

* [Self-healing tool calling](/docs/new/studio/chat.md#auto-healing-tool-calling) / web search and use [Unsloth as an API](/docs/basics/api.md).
* Connect your local models to any agent: [Claude Code](/docs/basics/claude-code.md), [Codex](/docs/basics/codex.md), [Hermes](/docs/integrations/hermes-agent.md) and more.
* Search + download + run any model like GGUFs, LoRA adapters, safetensors.
* [Auto inference parameter](/docs/new/studio/chat.md#auto-parameter-tuning) tuning and edit chat templates.
* [Export or save](/docs/new/studio/export.md) your model to GGUF, 16-bit safetensor etc.
* [Compare outputs](/docs/new/studio/chat.md#model-arena) with two different model side by side.

#### Training

* Train and [RL](/docs/get-started/reinforcement-learning-rl-guide.md) 500+ models \~2x faster with \~70% less VRAM (no accuracy loss)
* Supports full fine-tuning, pre-training, 4-bit, 16-bit and FP8 training.
* [Auto-create datasets](/docs/new/studio/data-recipe.md) from PDF, CSV, DOCX files. Edit data in a visual node workflow.
* Observability: Monitor training live, track loss, GPU usage, customize graphs
* Most efficient [**reinforcement learning**](/docs/get-started/reinforcement-learning-rl-guide.md) library, using 80% less VRAM for GRPO, [FP8](/docs/get-started/reinforcement-learning-rl-guide/fp8-reinforcement-learning.md) etc.
* [Multi-GPU](/docs/basics/multi-gpu-training-with-unsloth.md) works but a much better version is coming!

### **Latest models**

<table data-column-title-hidden data-card-wrap="false" data-view="cards"><thead><tr><th></th><th data-hidden data-card-cover data-type="image">Cover image</th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><h4>Qwen3.8</h4></td><td><a href="/files/T7cO71XRMo56f8iAJlTI">/files/T7cO71XRMo56f8iAJlTI</a></td><td><a href="/pages/CLyZKmpoJZpdaJXhLW4v">/pages/CLyZKmpoJZpdaJXhLW4v</a></td></tr><tr><td><h4>Meta Muse Glimmer</h4></td><td><a href="/files/6Mfar7OZnC0seQ85ClWM">/files/6Mfar7OZnC0seQ85ClWM</a></td><td></td></tr><tr><td><h4>Kimi K3</h4></td><td><a href="/files/TmfHDmv3BQb1Nfu0j133">/files/TmfHDmv3BQb1Nfu0j133</a></td><td><a href="/pages/WXhlrui6wK2vphF835XS">/pages/WXhlrui6wK2vphF835XS</a></td></tr><tr><td><h4>DeepSeek V4</h4></td><td><a href="/files/85y4U7RWZAZ0QTmgRGvX">/files/85y4U7RWZAZ0QTmgRGvX</a></td><td><a href="/pages/2f4eyCpdyRknNuEtv22n">/pages/2f4eyCpdyRknNuEtv22n</a></td></tr><tr><td><h4>Qwen3.6</h4></td><td><a href="/files/9q8wsfzbD8FrBu5tMwyp">/files/9q8wsfzbD8FrBu5tMwyp</a></td><td><a href="/pages/NpuhjPsxi8BKhuS8nnyY">/pages/NpuhjPsxi8BKhuS8nnyY</a></td></tr><tr><td><h4>GLM-5.2</h4></td><td><a href="/files/INMF5VptPzi2sTVbB02o">/files/INMF5VptPzi2sTVbB02o</a></td><td><a href="/pages/cZiZ00cwk1GGz1O1TOHo">/pages/cZiZ00cwk1GGz1O1TOHo</a></td></tr><tr><td><h4>Gemma 4</h4></td><td><a href="/files/Hi2ZAIfyCNvFganYz8Dk">/files/Hi2ZAIfyCNvFganYz8Dk</a></td><td><a href="/pages/VnmWq1kNppQrTqCI6aLH">/pages/VnmWq1kNppQrTqCI6aLH</a></td></tr><tr><td><h4>MiniMax M3</h4></td><td><a href="/files/RdQBx7sOTMt9KSvTW1BB">/files/RdQBx7sOTMt9KSvTW1BB</a></td><td><a href="/pages/hDMe4SBsxYeSiKWmNuP7">/pages/hDMe4SBsxYeSiKWmNuP7</a></td></tr><tr><td><h4>DiffusionGemma</h4></td><td><a href="/files/Te5bV0YXetWmaOCpjMDw">/files/Te5bV0YXetWmaOCpjMDw</a></td><td><a href="/pages/vTAENqjMpaMcreC9lp4b">/pages/vTAENqjMpaMcreC9lp4b</a></td></tr></tbody></table>

### **Video Demo**

{% embed url="<https://www.youtube.com/watch?v=_1hgTTuber4>" %}

{% columns %}
{% column width="50%" %}
{% content-ref url="/pages/OktH76Rsg2WQ12B4KR5H" %}
[Unsloth Updates](/docs/new/changelog.md)
{% endcontent-ref %}

{% content-ref url="/pages/gEugERiAw2ztDNt98JVR" %}
[Inference & Deployment](/docs/basics/inference-and-deployment.md)
{% endcontent-ref %}
{% endcolumn %}

{% column width="50%" %}
{% content-ref url="/pages/55c8159250801d9ea2207b9eb88a9a11b331d3ad" %}
[Unsloth Start](/docs/integrations/unsloth-start.md)
{% endcontent-ref %}

{% content-ref url="/pages/QznsvWxKKvrY6PdiByzz" %}
[Dynamic 3.0 GGUFs](/docs/basics/dynamic-3.0-ggufs.md)
{% endcontent-ref %}
{% endcolumn %}
{% endcolumns %}

<figure><img src="/files/loMei7rYNgzP5dknOQWu" alt="" width="188"><figcaption></figcaption></figure>


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://unsloth.ai/docs/docs.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.