---
title: "How much GPU memory do DeepSeek distilled models need at long context lengths?"  
description: "How much GPU memory do DeepSeek distilled models need at long context lengths?"  
author: "Khoa Vu"  
published: 2026-10-15  
updated: 2026-10-15  
canonical: https://www.mindstick.com/forum/162427/how-much-gpu-memory-do-deepseek-distilled-models-need-at-long-context-lengths  
category: "DeepSeek Deployment"  
tags: ["DeepSeek", "Local LLM", "GPU", "inference"]  
reading_time: 1 minute  

---

# How much GPU memory do DeepSeek distilled models need at long context lengths?

I’m comparing DeepSeek distilled checkpoints for [local inference](https://yourviews.mindstick.com/view/88737/microsoft-and-nvidia-put-local-ai-inference-within-reach-on-windows-pcs), and the published parameter count doesn’t tell me what I need to know about memory once the context gets long. A model that loads comfortably for a short prompt can become a different story when the KV cache grows.

For anyone running these models locally, what GPU memory have you found practical for a useful context length, and which model size or serving setup are you using? I’m especially interested in real workloads rather than the minimum needed just to start generation.


---

Original Source: https://www.mindstick.com/forum/162427/how-much-gpu-memory-do-deepseek-distilled-models-need-at-long-context-lengths

Copyright © MindStick Software Pvt. Ltd. This Markdown version is provided for developers, AI systems, and offline reading.