Concise monthly summary for March 2026 focusing on key accomplishments, bugs fixed, and impact across flashinfer-ai/flashinfer and jeejeelee/vllm. Highlighted reliability improvements for AutoTuner, expanded MXFP8 MoE capabilities, and test coverage enhancements enabling broader production readiness.

February 2026 monthly performance summary for jeejeelee/vllm and flashinfer-ai/flashinfer. Delivered cross-repo FP8/MXFP8 quantization enhancements, MoE optimization improvements, and stability fixes that enable faster, more reliable FP8/MXFP8 inference and easier adoption of MXFP8 checkpoints. Highlights include LoRA FP8 compatibility improvements, MXFP8 dense-model support with flashinfer mm_mxfp8 integration, a Nemotron TP4/B200 fused MoE config, a FlashInfer autotuner reshaping bug fix, and the new MXFP8 GEMM API (mm_mxfp8) with Cutlass. These changes drive higher throughput, lower latency, and greater deployment readiness for ModelOpt MXFP8 workloads.

January 2026 focused on delivering flexible, efficient inference capabilities for Nemotron-H/Nano models in jeejeelee/vllm, along with reliability improvements and benchmarking enhancements. The work emphasizes business value through device-specific optimizations and robust quantization handling, enabling faster deployment and more accurate performance assessments across configurations.

December 2025 performance highlights for flashinfer-ai/flashinfer and jeejeelee/vllm focusing on business value and technical achievements. The month delivered new acceleration and adaptability capabilities, along with robust validation; no critical bug fixes were reported this period.