---
title: "Discussion on \"LoRA, QLoRA, or Distillation? A No-Nonsense Guide to Choosing\" | Hashnode"
description: "Discussion on \"LoRA, QLoRA, or Distillation? A No-Nonsense Guide to Choosing\". If you've ever tried to fine-tune a large language model on normal hardware, you know the wall you hit fast. A 7-billion-parameter model trained the old-fashioned way can eat 100+ GB of GPU memory. Mo"
url: "https://hashnode.com/posts/lora-qlora-or-distillation-a-no-nonsense-guide-to-choosing/6aa99de3403009af3fad4e34"
---

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# [LoRA, QLoRA, or Distillation? A No-Nonsense Guide to Choosing](https://rpsarathy.hashnode.dev/lora-qlora-or-distillation-a-no-nonsense-guide-to-choosing?utm_source=hashnode&utm_medium=feed)

If you've ever tried to fine-tune a large language model on normal hardware, you know the wall you hit fast. A 7-billion-parameter model trained the old-fashioned way can eat 100+ GB of GPU memory. Mo

Sep 15 · 12 min read · rpsarathy.hashnode.dev  
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-   [#ai](https://hashnode.com/tag/ai)
-   [#rag](https://hashnode.com/tag/rag)
-   [#model](https://hashnode.com/tag/model)
-   [#llm](https://hashnode.com/tag/llm)
-   [#qlora](https://hashnode.com/tag/qlora)
-   [#lora](https://hashnode.com/tag/lora)

## Written by

[Partha](https://hashnode.com/@rpsarathy)

@rpsarathy · Cranbury, New jersey

  
[View profile](https://hashnode.com/@rpsarathy)

#AI #agents #langgraph, #mcp, #rag, #graphrag #llm #engineering-management

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