Java's virtual threads offer a lightweight concurrency model that is particularly effective for I/O-bound workloads. In Spring AI applications, calls to LLM APIs are typically blocking, tying up platform threads and limiting scalability. This benchmark compares traditional thread-per-request handling against virtual threads for synchronous LLM calls. Results indicate that virtual threads can handle a higher number of concurrent requests with lower latency and reduced memory overhead. The implementation leverages Spring's support for virtual threads, requiring minimal code changes. For teams building AI-powered services on the JVM, adopting virtual threads is a low-risk, high-impact optimization. This pattern is especially relevant as LLM integrations become a standard part of enterprise applications.
Java virtual threads can significantly improve throughput and reduce latency for blocking LLM I/O in Spring AI. This benchmark shows practical gains for AI service integrations.