Tag: Compressed Models

In the deployment of enterprise autonomous agent swarms, running models at full 16-bit floating-point precision (FP16 or BF16) creates massive hardware and financial friction. Serving a 70B parameter model at FP16 requires approximately 140 gigabytes of VRAM—demanding multiple interconnected enterprise GPUs (such as dual NVIDIA A100/H100 nodes), driving up cloud hosting costs, and capping concurrent […]