LLM Gateway
LLM Gateway provides developers with a central hub to route, manage, and monitor large language model requests across multiple providers, while tracking usage costs and performance metrics.
About this tool
LLM Gateway is built for developers who need a unified point of control for large language model interactions. It accepts incoming LLM requests, directs them to the appropriate provider, and returns the routed response, simplifying integration across heterogeneous AI services.
Beyond routing, the platform offers tools to manage API credentials, compare latency between providers, and keep an eye on spending. By consolidating these functions, developers can focus on application logic rather than the operational details of each model vendor.
What you can do
Unified Request Routing
Incoming LLM calls are automatically directed to the selected model provider, allowing developers to send a single request format regardless of the underlying service.
API Key Management
All provider credentials are stored and controlled in one place, giving developers a single dashboard to add, update, or revoke keys without editing code.
Cost and Performance Monitoring
The system records usage costs and measures latency for each request, presenting side‑by‑side comparisons that help teams optimise spending and response times.
Who is it for?
- A SaaS platform that offers AI‑generated content can switch between OpenAI and Anthropic models based on cost or latency, using LLM Gateway to handle the provider change without redeploying code.
- An internal tool that tracks API usage can pull cost data from LLM Gateway to generate monthly expense reports for budgeting and chargeback purposes.
- A development team testing new prompts can route the same request to multiple providers simultaneously, then compare latency and output quality through the monitoring dashboard.
Before you choose
Developers should verify how API keys are stored and whether the platform meets their organization’s security policies before uploading credentials.
Understanding the granularity of cost tracking is important; users need to confirm whether the reported figures align with each provider’s billing model.
Frequently asked questions
Can I add more than the three listed providers?
The current integration list includes OpenAI, Anthropic, and Google. Adding additional providers would require checking the platform’s roadmap or contacting support to see if custom connectors can be built.
How does LLM Gateway handle latency differences between providers?
The monitoring component records response times for each request and presents a comparative view, allowing developers to see which provider delivers faster results for specific workloads.
Is there a way to set usage limits per provider?
While the system tracks cost and usage, setting hard limits is not described in the available facts. Users should explore the management console to see if quota controls are offered or consider implementing external safeguards.
Check the official website for current features, pricing, and terms.
Similar tools
Helicone
OtherHelicone provides developers and enterprises with a monitoring layer for AI services.
Lunary
OtherLunary is an open‑source platform that helps developers monitor, debug, and improve large language model applications.
BoostRail
OtherBoostRail delivers an AI model service that can accept text, image, and video inputs, process them, and return the same media type as output.
OpenRouter
CodingOpenRouter gives developers one OpenAI-compatible API and one credit balance to access hundreds of AI models from many providers, with routing and fallbacks.
Vapi
AutomationVapi is a developer platform for building voice AI agents that handle phone and web calls, combining speech recognition, an LLM and speech synthesis.
Inference
OtherInference.net is aimed at AI‑native teams that require a reliable environment for production workloads.