The Neural Maze

Training a Reasoning Model on Consumer Hardware with GRPO and vLLM

The post introduces a hands‑on lab that trains a reasoning‑focused language model on consumer‑grade hardware using Group Relative Policy Optimization (GRPO). Unlike traditional PPO, GRPO discards the heavyweight critic model and scores a batch of responses relative to each other, dramatically cutting VRAM usage. The authors demonstrate the workflow with Unsloth and vLLM to eliminate the double‑memory generation bottleneck and accelerate fine‑tuning. By the end, readers can replicate a full reasoning model training loop without a GPU cluster.