Unify requests
Normalize authentication, models and response contracts.
Choose your path
Design model routing, AI gateways, fallback strategies, load balancing and rate-limit controls for reliable LLM applications.
Start with the decision, move into implementation and finish with production checks.
Normalize authentication, models and response contracts.
Select models by capability, cost, latency and availability.
Apply rate limits, queues, budgets and circuit breakers.
Track route decisions, fallback reasons and task success.
The control layer between applications and model providers.
Open guideCapability-aware routing policies for multi-model applications.
Open guideOne request contract across multiple providers and models.
Open guideSeparate retries, provider failover and quality fallback.
Open guideProtect throughput without creating cascading failures.
Open guideRoute normal traffic to the default model and fail over only when the request remains within budget and quality constraints.

Compare Gemini 4 Hydrogen and Gemini 4 Carbon on speed, benchmarks, context window, pricing, coding, research, cybersecurity, and API access.

Explore MiniMax H3-Image’s native 16MP output, 16-reference editing, Standard vs Highspeed latency, API pricing, and deployment limits.

Explore the Muse Spark 1.4 OpenCode listing, official API status, potential upgrades, Contributor pricing, and available alternatives.
An LLM gateway centralizes authentication, routing, observability, limits and provider abstraction for model requests.
No. Routing chooses the best initial route; fallback selects another compatible route after a defined failure or quality condition.