Google used Gemini 4 Argon to speed up graph mining and TPU kernels
Google's graph mining teams used Gemini 4 Argon with Antigravity's Teamwork agent to compress months of RDMA networking and TPU kernel work into hours, with FarArray up to 180x faster.
Today, we shared how Google’s Graph Mining and Graph Learning teams used Gemini 4 Argon with Teamwork agent in @GoogleAntigravity to solve a different class of internal engineering bottleneck: compressing months of low-level RDMA networking and custom TPU kernel development into hours. Specifically, improvements include accelerated graph algorithms with FarArray (up to 180x faster, 22x less RAM) and custom TPU kernels for Graph Neural Networks that run 8–15x faster than native JAX with massive HBM savings. For me, this update is a full-circle experience: Graph Mining contributed deeply to Gemini Data via deduping and data curation over time, and now Gemini is giving back by scaling and improving Graph Mining library! This is also a close collaboration amongst our Graph Mining and Teamwork teams, together with the Antigravity and Gemini teams. Congratulations! Read the full blog: https://antigravity.google/blog/gemini-4-argon-trillion-edge-graphs-and-tpu-kernels