February 2026: Delivered significant quantization workflow enhancements and new model support across multiple repos, enabling faster experimentation, broader model compatibility, and improved reliability. Improvements focus on quantization usability, device handling, and model map integration, with scalable configurations and clearer calibration workflows.

January 2026 monthly summary for the pytorch/ao repository. Focused on strengthening quantization tooling, improving test infrastructure, and streamlining documentation. Delivered features to parallelize AWQ tests, enhanced user guidance for model quantization with new examples and performance benchmarks, consolidated the observer steps enum for clarity, and removed outdated AQT workflow documentation. These efforts improve test throughput, provide clearer APIs and guidance for quantization workflows, and reduce maintenance overhead.