A lot of work goes into serving a model efficiently. For the Nemotron 3 Ultra NIM, our engineers tuned caching, memory, parallelism, decoding and more. On four B200 GPUs, those optimizations supported up to 2.5x more concurrent users while maintaining 50 TPS/u

A lot of work goes into serving a model efficiently. For the Nemotron 3 Ultra NIM, our engineers tuned caching, memory, parallelism, decoding and more. On four B200 GPUs, those optimizations supported up to 2.5x more concurrent users while maintaining 50 TPS/user. Read the engineering deep dive → 📷 ↧ How Full-Stack NIM Optimizations Deliver 2.5x More Users on Nemotro... Deploying a large language model is only the first step toward production-ready serving. Production teams also need to serve as many concurrent users as possible on available GPU infrastructure while…