The real value of tiny-vLLM isn't the engine — it's what it proves about vLLM's overhead

Everyone will look at tiny-vLLM as a deployment option. That's the wrong take. Its value is as a existence proof: a functional inference engine in ~1000 lines of C++/CUDA. The delta between its performance and vLLM's is a direct measure of what Python, Pydantic, and abstraction layers cost you. Run the benchmark.