TensorRT-LLM

Why we included this project

If you are serving large language models on NVIDIA GPUs and care about throughput and latency, this is one of the strongest inference backends around. You define the model in Python and it compiles down to kernels tuned for specific GPU generations, which is why it powers a lot of real production serving rather than just research demos. The bundled Python and C++ runtimes handle the actual orchestration, so you can go from a checkpoint to a running, batched service without wiring up a separate serving layer. Multi-GPU and multi-node support is built in, which matters for frontier-sized models or heavy request loads. For anyone picking an inference engine for a serious GPU deployment, this deserves a spot on the benchmark list.