At Superhuman (formerly Grammarly), a fine-tuned language model corrects grammatical errors for millions of monthly users, served with vLLM on CoreWeave's dedicated inference. Consumer scale stresses everything: throughput, latency, correctness, and cost. This talk covers how the team pressure-tests a serving setup against those requirements, vLLM tuning, and where dedicated inference and fully managed inference platforms converge or diverge. Beyond benchmarks, the team also validates in production with A/B tests. Expect an overview of how the model works and how serving is architected at Superhuman.
Speakers: Christoph Stuber, Software Engineer - ML Platform, Grammarly
