Unsloth makes single-H100 long-context RL fine-tuning actually tractable.

New batching algorithms enable ~7x, up to 12x+, longer-context GRPO training with no accuracy or speed penalty versus optimized FA3 and chunked-loss setups (Unsloth Docs). Qwen3-8B GRPO reaches 110K context on one 80GB H100 via vLLM plus QLoRA. For solo builders doing reasoning RL, long-context was previously off the table on a single GPU. Pair it with group-relative advantage, no critic network, to keep memory low. This is the kind of thing that quietly widens what one person can train.