LimX Dynamics updated the open-source FluxVLA Engine V2 technical report, adding online reinforcement-learning post-training, broader simulation evaluations, inference optimization, and deployment testing across ALOHA, Rebot, dual-arm Franka, and LimX Oli. The project reports that SmolVLA improved by 10.0 percentage points on LIBERO-10 and 15.4 points on ten RoboTwin Clean tasks after task-specific PPO post-training, while optimized inference paths across eight model-device combinations ran 2.31 to 9.64 times faster. The stack also supports multiple VLA architectures, including OpenVLA, π0.5, DiT4DiT, GR00T, and API-only policies, through shared data, training, evaluation, inference, and deployment workflows.