- Deploying C++ ports yields a single shared library (66 MiB) instead of a multi-gigabyte Python virtualenv (9.1 GiB for vLLM), with predictable memory usage.
- vllm.cpp achieves throughput parity or slight advantage over vLLM across concurrency levels, with token-for-token identical output and lower peak memory (24.88 GiB vs 28.18 GiB).
- depth-anything.cpp runs 1.31x faster than PyTorch on CPU while using 27% of the memory, thanks to caching positional embeddings that were recomputed unnecessarily.
- face-detect.cpp and voice-detect.cpp prioritize exact output matching (cosine 1.0, pixel-level accuracy) over speed, enabling drop-in replacement without re-enrolling biometric templates.