---
title: "Comment by Ali Muwwakkil on \"Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide\" | Hashnode"
description: "We recently found that teams often overlook the importance of token management when fine-tuning LLMs like GPT. Tokens aren't just data -they're the currency of"
url: "https://hashnode.com/posts/llm-fine-tuning-lora-qlora-guide-2026/69e19495d1a398fc0c989098/comment/69e19eb025940e8d82feb0a5"
---

[Discussion](https://hashnode.com/posts/llm-fine-tuning-lora-qlora-guide-2026/69e19495d1a398fc0c989098)

Comment [Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide](https://hashnode.com/posts/llm-fine-tuning-lora-qlora-guide-2026/69e19495d1a398fc0c989098)

[Ali Muwwakkil](https://hashnode.com/@enterpriseaileadersh)

[Apr 17](https://hashnode.com/posts/llm-fine-tuning-lora-qlora-guide-2026/69e19495d1a398fc0c989098/comment/69e19eb025940e8d82feb0a5)

We recently found that teams often overlook the importance of token management when fine-tuning LLMs like GPT. Tokens aren't just data -they're the currency of your model's understanding. Efficient token usage can drastically reduce both time and cost. In our work with enterprise teams, we've seen a 30% decrease in resource consumption just by optimizing tokenization strategies. This often involves customizing tokenizers to handle domain-specific jargon effectively, which can be a game-changer in reducing complexity and improving accuracy. - Ali Muwwakkil (ali-muwwakkil on LinkedIn)