
6/26/2026
What this post added
This post details how Fireworks provides the inference and rollout layer for large-scale distributed reinforcement learning, enabling Cursor to run RL across multiple global clusters. Key capabilities include cross-region model updates with significant transfer size optimization, minutes-level synchronization staleness, stable rollout fleets for MoE models, low-latency inference during training and evaluation, and reuse of production inference for RL sampling. This allows for accelerated RL cycles without dedicated inference infrastructure.