unslothai/unsloth

How can I increase the GPU utilization while training / finetune an LLM with unsloth

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#3957 opened on Feb 1, 2026

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help wanted

Description

I was fine-tuning a gemma3 4b model with unsloth with a custom dataset in Colab, but when I observed the GPU utilization, it was very low. Is there a way to fully utilize it, maybe use multiple processes?

Here is the Colab notebook I am using: https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_(4B).ipynb

Here is a sc I got while training: https://drive.google.com/file/d/1o3P-ORRJPACbGgOglfkbkoj1fV4VahZu/view?usp=sharing

Any help on this would be appreciated Thanks Dinusha

Contributor guide

Tech stack
pythonpytorch
Domain
machine learning
Issue type
performance
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
under 1 hour
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
needs maintainer response
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
familiarity with PyTorchbasic understanding of LLM fine tuning
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
30
Research direction
Review the linked Colab notebook to identify potential bottlenecks like small batch sizes or data loading issues. Suggest increasing batch size or using gradient accumulation. Check unsloth documentation for performance optimization tips.