Best Practices Guide for Customizing Gemini Models via Reinforcement Learning (RL)
Google, Friday, September 25th, 2026
Google Cloud published best practices for using its managed RL fine-tuning service to adapt Gemini models with custom reward functions.
Google Cloud detailed best practices for its managed reinforcement learning fine-tuning (RLFT) service, which lets customers adapt Gemini models using a reward function they define rather than labeled training examples.
The approach targets tasks that are hard to demonstrate but easy to score, such as generating correct SQL for an unfamiliar schema.
At each training step the service generates multiple candidate responses, scores them against the customer's reward, and nudges the model toward higher-scoring outputs while staying close to the base Gemini model.
The RL infrastructure is fully managed, so the customer's main task is designing the reward.