March 2026 monthly summary for the modular/modular repository focusing on Qwen3 embeddings and transformer optimization. Implemented normalization for Qwen3 embeddings to improve accuracy and align with PyTorch standards, and simplified transformer layer logic to boost performance. Updated verification pipeline thresholds to reflect improved embedding accuracy, reducing false positives and improving reliability. Fixed a missing normalization issue linked to a broader PR, and achieved alignment with upstream PyTorch expectations, contributing to a more robust embedding and inference path.

January 2026 performance highlights: Delivered Qwen3 Embedding Model Support in the MAX pipeline for modular/modular, introducing a dedicated embedding architecture and embedding-generation pipeline, enhancing model diversity and retrieval quality. Implemented registry improvements to resolve architecture conflicts between generative and embedding models and expanded verification coverage to ensure reliability across multiple model sizes.