AI agents can complete inference engineering tasks locally, but production correctness is much harder—end-to-end serving tests catch failures that other tests miss, exposing a critical gap between development and deployment.
SWE-Serve is a benchmark with 53 real production tasks from SGLang that tests whether AI agents can implement inference serving features correctly—not just locally, but in production. It reveals a major gap: one-third of code changes that pass unit tests fail end-to-end serving tests, showing that current agents struggle with production-grade correctness.