Cut GRPO RL fine-tuning VRAM 50–90% with Unsloth to train reasoning models on a single mid-tier GPU

Unsloth Documentation·medium signal

Unsloth reduces VRAM for GRPO reinforcement-learning fine-tuning by 50–90% versus standard Flash-Attention-2 setups, enabling gpt-oss-20b GRPO training in 15GB VRAM (free on Colab) and 1.2–1.7× longer context with no slowdown. GRPO uses group-based reward comparison as an on-the-fly baseline, eliminating the separate memory-hungry value model.