Scaling Agentic RL: High-Throughput Agentic Training with Tunix

Google's Tunix now targets scalable agentic RL with asynchronous rollouts and decoupled producer-consumer pipelines.

The update aims to reduce idle TPU time and improve throughput for multi-step LLM agent training.

Continuous, domain-specific metrics and lightweight observability help surface bottlenecks during training.

The library integrates with high-concurrency rollout engines such as vLLM-TPU and SGLang-Jax.