September 2025 — Performance and reliability improvements across two major repos. Focused on build hygiene in tt-metal and enhanced error diagnostics in llama.cpp to improve debuggability and user feedback.

August 2025 highlights for tenstorrent/tt-metal: automated packaging workflow, resolved dependency conflicts, and corrected packaging gaps to support llama.cpp builds. These changes reduce manual steps, improve installation reliability, and enhance cross-component stability, enabling faster and more predictable releases.

Month: 2025-07 — Focused on delivering a core backend operation in the tt-metal backend, specifically the TTNN AddMM operation, to enable more versatile neural network workloads on the Metal backend. Key accomplishments include delivering a functional equivalent of torch.addmm for TTNN, with support for various data types and configurations, and aligning changes with code reviews and upstream requests. Notes on impact and scope: This work expands the capabilities of tenstorrent/tt-metal to support combined multiply-add patterns directly on Metal, reducing the need to move data between CPU and GPU backends for common neural network layers, and enabling more end-to-end PyTorch workflows on mobile/embedded devices where Metal is the target backend. Commits associated with this delivery: ec7173757f591d1295390d139decab8c988dc129, 243c44fc36ee5ae54578ea2c25df2a0d73625431