Venky focused on expanding performance testing coverage for the TensorRT-LLM repository, building a suite of tests for the Llama-3.1-Nemotron-8B-v1 model across both PyTorch and TensorRT backends. Using Python and YAML, Venky integrated configurable test cases that varied input and output lengths, enabling detailed benchmarking of latency and throughput. The work included updating test configurations to support repeatable runs by specifying model paths, which improved the reliability of performance regression detection. By strengthening CI/CD pipelines and model integration, Venky’s contributions provided deeper visibility into model performance and supported faster, more reliable iteration for deployment readiness.