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SGLang is announced as the native rollout engine for Miles v0.1, an open-source reinforcement learning framework for LLMs and multimodal models, aimed at improving throughput, cache efficiency, and stability in RL training at scale.
Prime-rl adds a first-class algorithms layer with six built-in RL algorithms (GRPO, MaxRL, OPD, OPSD, SFT, ECHO), making it easier to implement custom algorithms with a single file.
Z. ai has open-sourced its RL infrastructure, the slime framework, which enabled efficient OPD post-training of GLM-5.2 in about two days. slime is an LLM post-training framework for RL scaling that integrates Megatron and SGLang, and has been battle-tested by frontier models like GLM, Qwen, DeepSeek, and Llama.