Monthly summary for 2026-05 highlighting key deliverables, major fixes, and impact for jeejeelee/vllm. Focus on performance, scalability and technical excellence.

April 2026 monthly summary for flashinfer-ai/flashinfer: Delivered routing_replay_out support for MoE kernels to enable routing replay in RL training workflows. The feature adds a per-token routing replay buffer to MoE kernels, enabling inference engines to return the selected expert IDs alongside outputs, with CUDA graph pre-allocation compatibility. Python API and C++ kernel changes were implemented to support pre-allocated buffers, ensuring zero overhead when routing_replay_out is None. No major bugs fixed this month; focus was on delivering end-to-end replay capability and improving reproducibility for RL experiments and integration with vLLM-style pipelines.

February 2026: Delivered key enhancements in jeejeelee/vllm. Implemented Marlin model no-activation and multiplication support to broaden quantization and processing capabilities. Fixed shared expert input propagation in latent MoE, boosting inference accuracy and stability. These changes extend model applicability, improve reliability, and deliver tangible business value through more efficient quantization and robust MoE inference.

Monthly summary for 2026-01: Focused on delivering non-gated MoE support for jeejeelee/vllm with FP8/INT8 tensor formats using Marlin and NVFP4 CUTLASS. Delivered end-to-end feature work, including new tests and adjustments to activation functions, weight handling, and quantization to enable non-gated MoE architecture and potential performance improvements in low-precision MoE workloads. This work lays the groundwork for scalable, cost-efficient inference on large models and strengthens the MoE code path with robust testing.

December 2025 monthly summary for repository kvcache-ai/sglang. Focused on delivering substantial features to improve model efficiency and expand quantization capabilities, while stabilizing deployment configurations to reduce operational risk.