---
title: "Which DeepSeek distilled model is practical for coding on a 12GB GPU?"  
description: "Which DeepSeek distilled model is practical for coding on a 12GB GPU?"  
author: "Eetu Saarinen"  
published: 2026-10-21  
updated: 2026-10-21  
canonical: https://www.mindstick.com/forum/162659/which-deepseek-distilled-model-is-practical-for-coding-on-a-12gb-gpu  
category: "Local Language Models"  
tags: ["DeepSeek", "Local AI", "AI Coding", "GPUs"]  
reading_time: 1 minute  

---

# Which DeepSeek distilled model is practical for coding on a 12GB GPU?

I’m looking at DeepSeek’s distilled models for local coding help, but I’m unsure how to choose one for a GPU with 12GB of VRAM. A model that technically loads isn’t necessarily pleasant to use if responses crawl or it struggles with ordinary programming questions.

For people running these locally, which **[DeepSeek distilled model](https://www.mindstick.com/forum/162427/how-much-gpu-memory-do-deepseek-distilled-models-need-at-long-context-lengths)** has felt like a reasonable balance of coding quality and speed? I’d be interested in your runtime, quantization choice, and the kinds of tasks you tested—not just a benchmark score.


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Original Source: https://www.mindstick.com/forum/162659/which-deepseek-distilled-model-is-practical-for-coding-on-a-12gb-gpu

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