LLM Gateway

Product Introduction

1. LLM Gateway is an open-source API management platform designed to streamline interactions with multiple large language model (LLM) providers through a unified interface. It enables developers to route requests, manage API keys, and analyze usage metrics across services like OpenAI, Anthropic, Google Vertex AI, and others without code changes. The platform supports both self-hosted deployments and a cloud-hosted version, offering flexibility for diverse infrastructure needs.
2. The core value of LLM Gateway lies in its ability to simplify multi-provider LLM integration while providing granular cost and performance analytics. It eliminates vendor lock-in by standardizing API interactions, allowing teams to dynamically optimize model usage based on latency, cost, or accuracy. The platform also centralizes security and governance for AI workloads across enterprises and development teams.

Main Features

1. LLM Gateway provides a unified API interface fully compatible with OpenAI’s format, enabling seamless migration from existing implementations with only endpoint and key changes. This compatibility ensures integration with libraries like Python’s openai package and frameworks such as Next.js without requiring code rewrites. The API supports all major LLM features, including chat completions, streaming, and function calling.
2. The platform offers multi-provider connectivity, routing requests to over 15 supported providers, including OpenAI, Anthropic, Google AI Studio, Mistral AI, and Groq. Users can configure fallback models, load-balance between providers, and set custom retry policies to ensure reliability. Provider-specific API keys are stored securely and injected dynamically during request processing.
3. Real-time usage analytics track metrics such as token consumption, response latency, and cost per request across all integrated providers. Dashboards compare model performance trends, error rates, and budget utilization, with data retention periods varying by plan (3 days for Free, 90 days for Pro). Teams can export logs for custom analysis or compliance auditing.

Problems Solved

1. LLM Gateway addresses the complexity of managing multiple LLM providers with differing APIs, authentication methods, and rate limits. Developers previously had to write provider-specific code and manually track costs across platforms, leading to increased technical debt and operational overhead. The platform abstracts these complexities into a single configurable layer.
2. The product targets engineering teams and organizations scaling AI-powered applications across multiple models or regions. It is particularly valuable for enterprises requiring cost optimization, DevOps teams managing production LLM deployments, and startups iterating on model performance comparisons.
3. Typical use cases include A/B testing models for accuracy/cost trade-offs, implementing failover for high-availability applications, and centralizing monitoring of AI expenses. For example, a customer support chatbot can route simple queries to cost-effective models like GPT-3.5 while reserving GPT-4 for complex tasks.

Unique Advantages

1. Unlike alternatives like OpenRouter, LLM Gateway offers full self-hosting under an MIT license, giving enterprises complete control over data residency and compliance. The Pro plan removes gateway fees when using custom provider keys, unlike competitors that charge per-token fees regardless of deployment mode.
2. The platform introduces dynamic model orchestration, automatically routing requests to the optimal provider based on real-time latency metrics or cost rules. For example, requests from mobile devices in Asia can prioritize Google’s Tokyo servers, while European desktop users default to Mistral’s EU endpoints.
3. Competitive advantages include hybrid deployment options (self-hosted or cloud), enterprise-grade security with isolated key storage, and extensibility through custom integrations. The analytics engine provides deeper cost attribution, breaking down expenses by project, team, or API endpoint.

Frequently Asked Questions (FAQ)

1. What makes LLM Gateway different from OpenRouter? LLM Gateway allows full self-hosting with no restrictions under the MIT license, whereas OpenRouter operates solely as a hosted service. It provides real-time cost and latency analytics per request, while OpenRouter offers aggregated reports. The Pro plan eliminates gateway fees when using custom provider keys, unlike OpenRouter’s persistent per-token charges.
2. What models do you support? The platform supports all major proprietary and open-source models, including OpenAI’s GPT-4o, Anthropic Claude 3, Google Gemini, Mistral 8x22B, Groq Mixtral, and Perplexity pplx-70b. Self-hosted deployments can add custom models or regional providers through a plugin architecture.
3. What is your uptime guarantee? The cloud-hosted version guarantees 99.9% uptime with SLA-backed credits for enterprise contracts. Self-hosted deployments depend on the user’s infrastructure but benefit from built-in retries and failover to alternate providers during outages.