AI Model Router
Reach dozens of model providers through one OpenAI-compatible interface, route by price, latency, throughput and availability, and fail over in seconds — OpenRouter, LiteLLM and Vercel AI Gateway class routing is the cost and reliability layer for multi-model apps in 2026
Tool Interface
Interactive tool will be available soon
Features
- ✓ One key and one endpoint for hundreds of models, with no need to register dozens of vendor accounts
- ✓ Route by price, latency, throughput, availability or custom rules, with automatic fallback when the primary errors
- ✓ Unified billing and usage views that split spend by key, user, team and project, with budget cut-offs
- ✓ Covers multimodal and local models, routing to cloud providers or your own Ollama and vLLM from one gateway
- ✓ Self-hosted open-source gateways add audit logs, rate limits, caching and A/B splitting for enterprise governance
How to Use
- Scope the need: which models you need, whether data may leave your region, and your hard budget and latency targets
- Pick a form: hosted for convenience (e.g. OpenRouter), self-hosted open source for control (e.g. LiteLLM), platform gateways for ecosystem fit (e.g. Vercel AI Gateway)
- Point your base URL and key at the gateway, then configure routing policy, fallback chains, budgets and rate limits
- Go live, track cost, latency and error rates per model, and keep tuning routing rules with regression tests
FAQ
What is an AI model router?
A unified layer between your app and model vendors. You call different vendors' models with one OpenAI-compatible API and key, while the gateway handles routing, failover, rate limiting, caching, usage metering and budgets. Notable options include OpenRouter, LiteLLM, Vercel AI Gateway, Cloudflare AI Gateway, Portkey, Requesty, Inworld Router and TrueFoundry AI Gateway.
How is it different from calling vendors directly?
Calling vendors directly means changing code, keys and billing accounts for every model switch, plus writing your own retry logic when a provider rate-limits or goes down. A router collapses that: the same base URL and key reach many models, a failed primary switches to a backup vendor automatically, billing consolidates into one balance, and rate limits and budgets are set in one place. The trade-off is an extra network hop, so measure latency on critical paths.
What signals can drive routing?
Common signals include price, latency, throughput sorting, provider ordering, model fallback chains and data-policy filters (for example, refusing providers that retain your data), plus conditional routing based on user tier, query complexity or custom metadata. Some gateways let you express rules in CEL and ship built-in A/B testing with sticky user assignment.
Does it cost more?
Many hosted gateways add a markup over provider prices or charge a usage-based platform fee, though some offer zero markup with a subscription. The real savings come from routing itself: sending simple requests to cheaper small models, caching repeat requests and avoiding expensive periods usually saves far more than calling a flagship model directly. Turn on per-key and per-team usage views to quantify before optimising.
Is self-hosted open source viable?
Yes. Open-source gateways such as LiteLLM can be deployed yourself, map token pricing across 100+ providers, and track spend by key, user and team. Self-hosting keeps data on your network, lets you route to local Ollama or vLLM, and gives full control of auditing and rate limits — at the cost of running your own high availability and upgrades. Enterprises often pair a self-hosted gateway with a hosted one as a backstop.
Where is it most needed?
Multi-model or availability-sensitive setups: production chat and agent services, SaaS that switches models by user tier, batch inference on cheap models, and online businesses that must not break when a model fails. Model orchestration is also spreading in coding, where GitHub offered dynamic multi-model orchestration for Copilot CLI as a research preview in September 2026.