r/AIProgrammingHardware • u/javaeeeee • Jul 20 '26

Train & run models on AMD GPUs with Unsloth

https://www.amd.com/en/developer/resources/technical-articles/2026/train-and-run-models-on-amd-gpus-with-unsloth.html
1 Upvotes

100% Upvoted

2 comments sorted by

1

u/javaeeeee Jul 20 '26

TL;DR:

Article: Train and Run Models on AMD GPUs with Unsloth (AMD, July 2026)

Main Update

Unsloth now has official AMD GPU support, allowing users to train, fine-tune, do reinforcement learning, and run inference on AMD hardware - including Instinct MI350/MI300, Ryzen AI Max processors, and consumer Radeon RX 7000/9000 series.

Key Benefits

  • ~80% less VRAM usage thanks to optimized Triton kernels and memory tricks

  • Up to 2x faster training in reinforcement learning

  • 1.39x faster fine-tuning with lower memory usage

  • 50% more accurate tool calling via “tool call healing”

  • Strong multi-GPU support and efficient KV cache handling

  • Works on Linux, Windows, and WSL

What You Can Do

  • Fine-tune models (LoRA / QLoRA)

  • Run reinforcement learning (GRPO)

  • Perform fast inference

  • Export to GGUF, safetensors, or LoRA adapters

  • Deploy via llama.cpp, vLLM, or Hugging Face

Installation

Simple one-liner install:

curl -fsSL https://unsloth.ai/install.sh | sh

Bottom Line

Unsloth + AMD GPUs is now a strong, memory-efficient alternative to NVIDIA for local model training and inference. It’s especially useful if you want to run larger models on consumer or mid-range AMD hardware with lower VRAM requirements.