VeRL-Omni v0.2.0: Faster Diffusion RL and Stable Omni Training
A release focused on higher-throughput diffusion rollout, reusable omni adapters, and broader recipe coverage.
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verl on AMD: production-ready RL post-training on ROCm
RL post-training on AMD Instinct GPUs is here: a turnkey ROCm container, AITER-accelerated vLLM and SGLang rollout, and accuracy validated on both MI300 and MI350 series.
Faster Draft Model Training: verl-SpeCo 0.1.0 Adds Native DSpark Support and Unlocks Standalone Training
verl-SpeCo 0.1.0 adds native DSpark support and standalone draft model training, with reusable feature storage, seven algorithm backends, vLLM/SGLang integration, and GPU/Ascend NPU support.
Introducing verl-tinker: Your Tinker loop, your GPUs
Keep the Tinker Cookbook loop you know, and run SFT, RL, and distillation on verl-managed GPU workers you control.
Introducing the verl blog
verl now has its own blog. It exists so that the people who build features can explain them properly.