ishanjain1502/distributed-inference-engine

The 'distributed-inference-engine' project is a representative prototype for distributed LLM orchestration, but it lacks the scale, community, and technical differentiation required to survive in a hyper-competitive landscape. With only 3 stars and 1 fork over 90 days, it shows no sign of adoption. The problems it aims to solve—KV cache management and memory-bound backpressure—are already addressed at an industry-leading level by projects like vLLM (with PagedAttention), Hugging Face TGI, and NVIDIA's TensorRT-LLM. These established projects have thousands of contributors and deep integration with hardware accelerators. Furthermore, frontier labs and hyperscalers (AWS, Azure, GCP) provide managed inference services that render standalone, small-scale orchestration frameworks redundant for most enterprise users. The displacement horizon is set at 6 months because the project is already effectively displaced by more mature open-source alternatives.