vLLM adds Day-0 support for Recursive's Flint model
A sparse 2.5B-active architecture hitting 500 TPS on one GB200 shows how far inference efficiency now goes without speculative decoding, a benchmark point worth tracking against dense models of similar quality. Teams serving long-context workloads can run Flint in vLLM immediately in either NVFP4 or BF16. Builders evaluating open-weight model serving stacks should compare its throughput on their own GPUs.
