LLM Gateway
An LLM Gateway is a middleware infrastructure layer situated between the application layer and large language model services, used to centrally manage access to multiple large language models. Core capabilities include request routing and load balancing (distributing traffic across different models or providers), identity authentication and access control, usage metering and billing management, as well as request rate limiting, logging, and observability support. LLM Gateways help abstract underlying model differences, reduce application coupling to specific models, and serve as an important component of enterprise-grade AI application architecture.
Timeline (last 90 days)
An LLM Gateway is a middleware layer between applications and model providers, whose typical capabilities include unifying the API protocols of multiple providers, centrally managing API keys, budgeting and rate limiting by team or project, logging usage and costs, caching repeated requests, and automatically switching upstreams on failure.
Installing the gateway software itself does not come with any model quota, and upstream access must be arranged separately.
Sending non-desensitized tenant prompts to third-party gateways introduces data privacy and compliance risks.
Numbers measured directly against a host represent the hardware's own figures, while numbers measured through a gateway represent the real user experience including queuing and routing, and the two should not be mixed into the same table.
The underlying mechanism of multi-model collaboration typically relies on a Model Router or LLM gateway component to dynamically distribute requests based on task type, token cost, and latency requirements.
All Facts (6)
LLM网关提供请求频次控制、Token消耗统计、缓存命中、日志记录和成本预估等功能
85%UnverifiedAn LLM Gateway is a middleware layer between applications and model providers, whose typical capabilities include unifying the API protocols of multiple providers, centrally managing API keys, budgeting and rate limiting by team or project, logging usage and costs, caching repeated requests, and automatically switching upstreams on failure.
50%UnverifiedInstalling the gateway software itself does not come with any model quota, and upstream access must be arranged separately.
50%UnverifiedSending non-desensitized tenant prompts to third-party gateways introduces data privacy and compliance risks.
50%UnverifiedNumbers measured directly against a host represent the hardware's own figures, while numbers measured through a gateway represent the real user experience including queuing and routing, and the two should not be mixed into the same table.
50%UnverifiedThe underlying mechanism of multi-model collaboration typically relies on a Model Router or LLM gateway component to dynamically distribute requests based on task type, token cost, and latency requirements.
50%