Model Routing
Automatically send each request to the best available model based on cost, latency, quality, or throughput priorities across major AI providers.
FastRouter helps teams balance LLM traffic across providers with intelligent routing, automatic failover, and one OpenAI-compatible API. Route each request to the best available model for cost, latency, quality, or throughput while reducing provider lock-in, improving uptime, and keeping production AI workloads observable, governed, and easier to operate at scale.
Balance, monitor, and govern AI traffic across providers through one production-ready control plane.
Automatically send each request to the best available model based on cost, latency, quality, or throughput priorities across major AI providers.
Keep applications available during provider outages, rate limits, or model failures with centrally managed fallback lists and automatic rerouting.
Use one stable model alias while FastRouter applies policy-driven selection across prioritized models and providers behind the scenes.
Improve uptime with multi-provider redundancy, intelligent traffic routing, higher effective capacity, and 24/7 reliability for production workloads.
Track latency, uptime, error rates, and output quality across models and providers to catch regressions before users are affected.
Route workloads toward efficient models, enforce spend limits, and identify savings opportunities without sacrificing reliability or output quality.
FastRouter turns multi-provider LLM access into a resilient operating layer for production AI. Instead of hard-coding models or managing separate failover logic, teams can route traffic dynamically across 100+ models, monitor performance in real time, and enforce budgets and access controls from one place. The result is higher reliability, lower operational overhead, and smarter model usage.
See how production AI teams improve uptime, control costs, and simplify multi-provider operations.
"Excellent platform to test the latest LLMs for our use case. With new LLMs coming out every few weeks and benchmarks not giving the full picture, I rely on Fastrouter.ai to optimize my cost vs quality balance."
FastRouter gives teams one operational foundation for reliable, governed, multi-provider AI.
Route across OpenAI, Anthropic, Gemini, Grok, and more through one gateway.
Automatic fallback lists keep AI applications running through outages and rate-limit errors.
Optimize requests for cost, latency, throughput, or quality without manual tuning.
Control spend, roles, access, logs, and policies centrally across every team.
Infrastructure built for production AI operations.
FastRouter is built as an LLMOps platform for teams that need more than basic model access. Its control plane unifies routing, observability, experiment tracking, guardrails, evaluations, governance, and billing across 100+ models through one OpenAI-compatible API. The platform is designed for engineering, product, ML, and finance teams running production AI workloads that must remain reliable as model providers change, rate limits shift, and costs grow. By centralizing provider access and operational controls, FastRouter helps organizations move faster without creating brittle integrations, unmanaged spend, or fragmented monitoring across every AI vendor account.
LLM load balancing distributes requests across multiple models or providers instead of sending every call to one endpoint. With FastRouter, routing can optimize for cost, latency, output quality, or throughput. This helps teams avoid provider lock-in, reduce outages caused by rate limits or failures, and make better use of different models for different tasks.
Get clear guidance on routing, failover, governance, and cost control.
One integration across major model providers
Built for automatic failover and redundancy
Access limits, roles, logs, and guardrails
Share your routing, reliability, cost, or governance goals, and learn how FastRouter can support production AI workloads.
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