Unsloth Enables 7x Longer AI Training Contexts on Single GPU

Someone figured out how to train large language models with massively longer context windows without needing server farms. Unsloth now handles up to 7x longer contexts for reinforcement learning.

What this means practically:

• Train gpt-oss 20B with 20K context on a single 24GB GPU (previously impossible)
• Qwen3-8B GRPO reaches 110K context on an 80GB H100
• Works with Llama, Gemma, and most popular models

The magic comes from combining three techniques - weight-sharing with vLLM, Flex Attention, and async gradient checkpointing. They all stack together instead of conflicting.

Try it:

• GitHub: https://github.com/unslothai/unsloth
• Free notebooks: https://docs.unsloth.ai/get-started/unsloth-notebooks
• Full guide: https://unsloth.ai/docs/new/grpo-long-context

Pretty wild that someone can now fine-tune models with 100K+ context on hardware that costs less than a used car. Makes long-context RL training accessible to people running local setups instead of cloud bills.