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- # Glint Research
 
 
 
 
 
 
 
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  We teach tiny neural networks to think. Sometimes they surprise us. Sometimes they just output zeros.
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- ### Want to join our discord?
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- https://discord.gg/y2jTct6Cxv
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- ## Associates
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- We work with other folks who also enjoy the small life:
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- * [TeichAI](https://huggingface.co/TeichAI)
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- * [Armand0e](https://huggingface.co/armand0e)
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- * [Crownelius](https://huggingface.co/Crownelius)
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- * [Enderchef](https://huggingface.co/Enderchef)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- # Hey! You can support us!
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- <a href='https://ko-fi.com/F1F31YAC4I' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://storage.ko-fi.com/cdn/kofi6.png?v=6' border='0' alt='Buy Me a token at ko-fi.com' /></a>
 
 
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+ <p align="center">
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+ <img src="GlintResearchModelCardHeader.jpg" width="800">
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+ </p>
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+ <div align="center">
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+ <a href="https://discord.gg/y2jTct6Cxv" target="_blank"><img alt="Discord" src="https://img.shields.io/badge/Discord-Join%20the%20Community-5865F2?logo=discord&logoColor=white"/></a>
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+ <a href="https://ko-fi.com/F1F31YAC4I" target="_blank"><img alt="Ko-fi" src="https://img.shields.io/badge/Ko--fi-Support%20Us-FF5E5B?logo=ko-fi&logoColor=white"/></a>
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+ </div>
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+
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+ ---
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+
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+ # Glint Research
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  We teach tiny neural networks to think. Sometimes they surprise us. Sometimes they just output zeros.
 
 
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+ ---
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+
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+ ## What We Do
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+
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+ - Design and train million-parameter generative models
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+ - Study the behavior of small architectures under constrained compute
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+
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+ ---
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+
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+ ## Models
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+
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+ **Anthos** — Tiny Flower Generation
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+
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+ **Glint** — 1M Parameter Model Series
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+
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+ **Shard** — 10M Parameter Model Series
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+
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+ More models are in active development. Follow us to stay updated!
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+
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+ ---
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+
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+ ## Associates
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+
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+ We collaborate with other researchers and builders who share an interest in small models.
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+ <div align="center">
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+ <table style="border: none; border-collapse: collapse;">
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+ <tr>
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+ <td align="center" style="padding: 16px; border: none;">
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+ <a href="https://huggingface.co/TeichAI" target="_blank">
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+ <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/6837935ac3b7ffe0d2559ce9/-AxyvV4wfUY8uo87kNKkK.png" width="72" height="72" style="border-radius: 50%; object-fit: cover;" onerror="this.src='https://huggingface.co/front/assets/huggingface_logo-noborder.svg'"/>
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+ <br/><br/>
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+ <b>TeichAI</b>
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+ </a>
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+ </td>
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+ <td align="center" style="padding: 16px; border: none;">
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+ <a href="https://huggingface.co/armand0e" target="_blank">
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+ <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/wTsY5aBdcDk3Ldr9fSsQw.png" width="72" height="72" style="border-radius: 50%; object-fit: cover;" onerror="this.src='https://huggingface.co/front/assets/huggingface_logo-noborder.svg'"/>
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+ <br/><br/>
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+ <b>Armand0e</b>
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+ </a>
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+ </td>
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+ <td align="center" style="padding: 16px; border: none;">
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+ <a href="https://huggingface.co/Crownelius" target="_blank">
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+ <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/6969cc22e48357488a36a4fc/tvWSJ1KHdgh7faPM-p5e9.png" width="72" height="72" style="border-radius: 50%; object-fit: cover;" onerror="this.src='https://huggingface.co/front/assets/huggingface_logo-noborder.svg'"/>
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+ <br/><br/>
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+ <b>Crownelius</b>
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+ </a>
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+ </td>
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+ <td align="center" style="padding: 16px; border: none;">
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+ <a href="https://huggingface.co/Enderchef" target="_blank">
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+ <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/65d3d84d457647eb547ed73b/4yhQhLjJfsMzfdsfQwmwr.png" width="72" height="72" style="border-radius: 50%; object-fit: cover;" onerror="this.src='https://huggingface.co/front/assets/huggingface_logo-noborder.svg'"/>
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+ <br/><br/>
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+ <b>Enderchef</b>
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+ </a>
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+ </td>
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+ </tr>
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+ </table>
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+ </div>
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+ ---
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+
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+ ## Principles
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+
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+ **Transparency.** Every model we release includes architecture details, training configurations, loss curves, and known limitations. We do not publish numbers we cannot reproduce.
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+ **Efficiency.** We target few-GPU, short-run experiments. A model that trains in 8 hours on consumer hardware is more compact than one that requires a cluster.
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+ **Honesty about scale.** Small models have hard limits. We document them clearly rather than overstating capability.
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+
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+ ---
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+
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+ ## Community
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+
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+ Research is better with others. If you are working on small generative models, efficient training pipelines, or compact architectures and want to exchange ideas, we maintain an active Discord server.
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+
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+ <div align="center">
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+ <a href="https://discord.gg/y2jTct6Cxv" target="_blank">
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+ <img alt="Join the Discord" src="https://img.shields.io/badge/Discord-Join%20the%20Community-5865F2?style=for-the-badge&logo=discord&logoColor=white"/>
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+ </a>
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+ </div>
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+
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+ ---
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+
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+ ## Support
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+ Glint Research is an independent, self-funded effort. If you find the work useful, support via Ko-fi helps cover compute costs and keeps experiments running.
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+ <a href='https://ko-fi.com/F1F31YAC4I' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://storage.ko-fi.com/cdn/kofi6.png?v=6' border='0' alt='Buy Me a token at ko-fi.com' /></a>
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+
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+ ---
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+ <p align="center">
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+ Glint Research small models, honest results.
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+ </p>