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Unsloth Requirements

Here are Unsloth's requirements including system and GPU VRAM requirements.

System Requirements

Operating System: Works on Linux and Windows
Supports NVIDIA GPUs since 2018+ including and
Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20 & 50, A100, H100, L40 etc) GTX 1070, 1080 works, but is slow.
The official unsloth/unsloth is available on Docker Hub
Unsloth works on and GPUs! Apple/Silicon/MLX is in the works
If you have different versions of torch, transformers etc., pip install unsloth will automatically install all the latest versions of those libraries so you don't need to worry about version compatibility.
Your device should have xformers, torch, BitsandBytes and triton support.

Python 3.13 is now supported!

Fine-tuning VRAM requirements:

How much GPU memory do I need for LLM fine-tuning using Unsloth?

A common issue when you OOM or run out of memory is because you set your batch size too high. Set it to 1, 2, or 3 to use less VRAM.

For context length benchmarks, see .

Check this table for VRAM requirements sorted by model parameters and fine-tuning method. QLoRA uses 4-bit, LoRA uses 16-bit. Keep in mind that sometimes more VRAM is required depending on the model so these numbers are the absolute minimum:

Model parameters

QLoRA (4-bit) VRAM

LoRA (16-bit) VRAM