NVIDIA

Spotify and NVIDIA say TensorRT LLM cut generative-recommendation inference cost by up to 54%

Spotify Engineering and NVIDIA Engineering report moving LLM podcast recommendations from vLLM to TensorRT LLM after closing gaps in beam search, scoring and soft-token injection. They state up to 54% lower cost for beam-search workloads and up to 7% for scoring on a 1.7B Qwen3 model; Spotify says vLLM's beam search forced lower-tier GPUs at launch.

Why it matters A reminder to test the engine on the decoding method you actually use; the post is vendor-co-authored, gives no absolute costs, and puts its benchmark numbers in images, so the percentages are not transferable.