LLM API Gateway 2026: One Endpoint to Rule All Models
OpenAI, Claude, Gemini, local models - managing keys and endpoints for each is chaos. An LLM gateway unifies them behind one API. Here's how.
💡 What You Will Learn
OpenAI, Claude, Gemini, local models - managing keys and endpoints for each is chaos. An LLM gateway unifies them behind one API. Here's how.
📜 Table of Contents
The Multi-Model Mess
Production AI teams rarely use one model: they route cheap tasks to cheap models, use frontier models for hard ones, and switch vendors when prices change. Managing that manually - keys, endpoints, retries, budgets per provider - is exactly the chaos an LLM gateway removes.
What a Gateway Does
- One API for all providers (OpenAI-compatible interface).
- Key management: one key for your team, per-provider keys stored server-side.
- Routing: send requests to specific models or auto-route by rules.
- Fallback/retry: if one provider fails, try the next.
- Observability: logs, token counts, costs per request.
- Budget controls: caps per key, per team, per model.
The Open Source Gateways
LiteLLM (56,266 stars, 2026-08-14) - the de facto standard: a proxy that exposes 100+ providers (OpenAI, Anthropic, Gemini, Azure, Ollama, vLLM...) behind one OpenAI-compatible endpoint. Battle-tested, huge community, and the config is a single YAML. Start here.
one-api (36,372 stars) - the popular unified gateway in the Chinese ecosystem: multi-provider, token-based access, a clean admin UI for distributing keys to users.
new-api (45,082 stars) - a one-api fork with more providers, better dashboard, and pricing/metering features. The community's pick for reselling or team billing.
Kong AI Gateway (43,974 stars) - the enterprise-grade option: Kong's API gateway with AI plugins for routing, load balancing, and rate limits across LLM providers. Choose when you already run Kong.
Cloudflare AI Gateway - the managed option: one endpoint, caching, rate limiting, logging, and fallbacks across providers, with Cloudflare's edge network. Generous free tier.
The 15-Minute Setup (LiteLLM)
# config.yaml
model_list:
- model_name: gpt-4o-mini
litellm_params: {model: openai/gpt-4o-mini, api_key: os.environ/OPENAI_API_KEY}
- model_name: claude-sonnet
litellm_params: {model: anthropic/claude-sonnet-4, api_key: os.environ/ANTHROPIC_API_KEY}
- model_name: local-llama
litellm_params: {model: ollama/llama3.3}
litellm --config config.yaml --port 4000
# now: curl http://localhost:4000/v1/chat/completions with model=claude-sonnet
Your app code never changes when you swap providers - only the config.
FAQ
Is LiteLLM production-ready? Yes - thousands of companies run it in production; it powers many LLM platforms.
Does a gateway add latency? A few milliseconds of proxy overhead - negligible vs API latency.
Can I mix cloud and local models? Yes - that's a top use case: local for cheap/sensitive, cloud for hard.
Managed vs self-hosted? Cloudflare AI Gateway for zero ops; LiteLLM for control and zero per-request cost.
