I put 6 LLM guardrail tools inline and measured what they cost me. Here is the latency-vs-recall tradeoff.
A recent analysis compared six LLM guardrail tools, evaluating their performance based on latency and recall for detecting prompt injections and other security threats. The study found that tools like Future AGI's fi.evals scanners excelled in speed, operating under 10ms, making them suitable for inline use on production agents. Other tools, such as Lakera Guard, offered a low-effort hosted solution, while Meta's Llama Guard and NVIDIA's NeMo Guardrails provided flexibility for self-hosted deployments. The key takeaway is that the decision to use a guardrail tool hinges on its ability to meet latency requirements without sacrificing critical detection capabilities. AI
IMPACT Provides practical guidance for developers on selecting LLM security tools based on performance tradeoffs.