🛠️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 Blackwell RTX 50 and DGX Spark

  • Blackwell, RTX 50 and Unsloth

  • DGX Spark and Unsloth

• Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20 & 50, A100, H100, L40 etc) Check your GPU! GTX 1070, 1080 works, but is slow.

• The official Unsloth Docker image unsloth/unsloth is available on Docker Hub

  • Docker

• Unsloth works on AMD and Intel 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 here.

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
3B	3.5 GB	8 GB
7B	5 GB	19 GB
8B	6 GB	22 GB
9B	6.5 GB	24 GB
11B	7.5 GB	29 GB
14B	8.5 GB	33 GB
27B	22GB	64GB
32B	26 GB	76 GB
40B	30GB	96GB
70B	41 GB	164 GB
81B	48GB	192GB
90B	53GB	212GB
405B	237 GB	950 GB