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mistralai_Magistral-Small-2509-EXL3
ArtusDev/mistralai_Magistral-Small-2509-EXL3
mistralai_Magistral-Small-2509-EXL3 is a machine learning model from ArtusDev. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Sep 17, 2025
- Updated
- Oct 13, 2025
- SHA
- b4613210
Base models
Model card
From the Hugging Face model README
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<div class="container-dark">
<div class="card-dark card-dark-title">
<h1>ArtusDev/mistralai_Magistral-Small-2509-EXL3</h1>
<p class="subtitle">
EXL3 quants of <a href="https://huggingface.co/mistralai/Magistral-Small-2509" target="_blank">mistralai/Magistral-Small-2509</a> using <a href="https://github.com/turboderp-org/exllamav3/" target="_blank">exllamav3</a> for quantization.
</p>
<p class="subtitle">
Based on the HF conversion of the base Magistral model by <a href="https://huggingface.co/unsloth" target="_blank">@unsloth</a>: <a href="https://huggingface.co/unsloth/Magistral-Small-2509" target="_blank">unsloth/Magistral-Small-2509</a>.
</p>
</div>
<div class="card-dark">
<h2>Quants</h2>
<table class="styled-table">
<thead>
<tr>
<th>Quant</th>
<th>BPW</th>
<th>Head Bits</th>
</tr>
</thead>
<tbody>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/2.5bpw_H6" target="_blank">2.5_H6</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/2.5bpw_H6" target="_blank">2.5</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/2.5bpw_H6" target="_blank">6</a></td>
</tr>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/3.0bpw_H6" target="_blank">3.0_H6</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/3.0bpw_H6" target="_blank">3.0</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/3.0bpw_H6" target="_blank">6</a></td>
</tr>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/3.5bpw_H6" target="_blank">3.5_H6</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/3.5bpw_H6" target="_blank">3.5</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/3.5bpw_H6" target="_blank">6</a></td>
</tr>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/4.0bpw_H6" target="_blank">4.0_H6</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/4.0bpw_H6" target="_blank">4.0</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/4.0bpw_H6" target="_blank">6</a></td>
</tr>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/4.5bpw_H6" target="_blank">4.5_H6</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/4.5bpw_H6" target="_blank">4.5</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/4.5bpw_H6" target="_blank">6</a></td>
</tr>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/5.0bpw_H6" target="_blank">5.0_H6</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/5.0bpw_H6" target="_blank">5.0</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/5.0bpw_H6" target="_blank">6</a></td>
</tr>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/6.0bpw_H6" target="_blank">6.0_H6</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/6.0bpw_H6" target="_blank">6.0</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/6.0bpw_H6" target="_blank">6</a></td>
</tr>
<tr>
<td><a href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/8.0bpw_H8" target="_blank">8.0_H8</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/8.0bpw_H8" target="_blank">8.0</a></td>
<td><a class="fake-link" href="https://huggingface.co/ArtusDev/mistralai_Magistral-Small-2509-EXL3/tree/8.0bpw_H8" target="_blank">8</a></td>
</tr>
</tbody>
</table>
</div>
<div class="card-dark">
<h2>How to Download and Use Quants</h2>
<p>You can download quants by targeting specific size using the Hugging Face CLI.</p>
<details>
<summary>Click for download commands</summary>
<div class="details-content">
<b>1. Install huggingface-cli:</b>
<pre><code>pip install -U "huggingface_hub[cli]"</code></pre>
<b>2. Download a specific quant:</b>
<pre><code>huggingface-cli download ArtusDev/mistralai_Magistral-Small-2509-EXL3 --revision "5.0bpw_H6" --local-dir ./</code></pre>
</div>
</details>
<p>EXL3 quants can be run with any inference client that supports EXL3, such as <a href="https://github.com/theroyallab/tabbyapi" target="_blank"><b>TabbyAPI</b></a>. Refer to <a href="https://github.com/theroyallab/tabbyAPI/wiki/01.-Getting-Started" target="_blank">documentation</a> for set up instructions.</p>
</div>
<div class="card-dark">
<h2>Quant Requests</h2>
<div style="text-align: center; margin-top: 25px;">
<a href="https://huggingface.co/ArtusDev/requests-exl/discussions/new?title=[MODEL_NAME_HERE]&description=[MODEL_HF_LINK_HERE]" class="btn-purple" target="_blank">Request EXL3 Quants</a>
</div>
<p class="subtitle">
See <a href="https://huggingface.co/ArtusDev/requests-exl" target="_blank">EXL community hub</a> for request guidelines.
</p>
</div>
</div>
- License
- apache-2.0
- Languages
- en, fr, de, es, pt, it
- Created
- Sep 17, 2025
- Updated
- Oct 13, 2025