Do You Really Need a GPU to Guard Your LLM? CPU-Class Classifiers and Multi-Stage Pipelines for Safety Enforcement at Scale
A new research paper proposes GuardChain, a three-stage safety pipeline for LLM deployments that significantly reduces reliance on expensive GPU infrastructure. The study demonstrates that CPU-class classifiers can effectively handle the majority of in-distribution prompts, achieving near-peak accuracy at a fraction of the cost. While CPU classifiers struggle with out-of-distribution and adversarially obfuscated inputs, the proposed GuardChain pipeline integrates them with GPU-based models to recover these failures, offering a more cost-efficient approach to LLM safety enforcement at scale. AI
IMPACT Demonstrates a viable path to significantly reduce LLM deployment costs by leveraging CPU-class hardware for safety checks.