AI Gateway benchmark: Comparing security and performance

Large Language Models (LLMs) have revolutionized artificial intelligence by enabling applications such as content generation and linguistic tasks that previously required task-specific models, offering more scalability and adaptability. However, their creativity can lead to off-topic or undesirable outputs, posing challenges in enterprise settings like customer service. To address these issues, organizations employ LLM guardrails and AI gateways to align responses with business objectives and compliance. LLM guardrails regulate AI outputs but face scalability and operational challenges as they rely on static rules. AI gateways, however, offer a more centralized, infrastructure-level solution, ensuring consistent policy enforcement and reducing management complexity across AI applications. The market for AI gateways is limited, with some companies opting for traditional API gateways due to their flexibility. However, purpose-built AI gateways like TrustGate outperform in handling AI workloads, offering superior performance, scalability, and security compared to general API gateways. Benchmark results show TrustGate as the most efficient, with a high throughput and low latency, setting an industry standard for AI-first infrastructure.

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