reasoning tokens

Smarter reasoning with fewer tokens, trained on a single GPU

Training a model to reason smarter with fewer tokens, that's the kind of practical progress we like to see. The developer behind this Qwen3-4B project cut reasoning tokens by 44% while preserving knowledge and output style, all on a single GPU. That's not just efficient; it's a direct challenge to the assumption that better reasoning requires bigger compute. If you're curious how AI agents handled a different kind of optimization, our article "300K lines refactored for $4,000" explores that trade-off in a C codebase.