Deepgram improves Nova-3 speech-to-text efficiency on AWS trainium2

In offline, throughput‑oriented batch workloads the Trainium2 configuration delivered 11–70 percent more audio per dollar than Deepgram’s prior compute options, based on instance pricing at the time of evaluation. A custom Rust data‑parallel runtime eliminated Python interpreter overhead and added a 7.5 percent throughput gain over a multiprocessing Python baseline. These improvements lower costs for Deepgram’s customers and demonstrate that AWS Trainium can be an efficient platform for large‑scale voice AI inference.