Ranked comparison

LLM Router: Intelligent Model Selection for Every Request

An LLM router inspects each request and picks the best model based on task type, cost constraints, and latency requirements. No more hard-coding a single model for everything.

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Credit-based pay-per-use with token-settled billing. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

First success in 60 seconds

Step 01Sign up in 10 secondsGet 20 free credits Step 02Open your dashboardCreate API key Step 03Send first requestRun a sample

Why teams start here first

No monthly subscription

Pay-as-you-go credits

Start with trial credits, then buy only what you consume.

Failover safety

Production-ready routing

Auto fallback across providers when latency, quality, or reliability changes.

Data control

Your policy, your choice

BYOK and zero-retention mode keep training and storage scope explicit.

Single API experience

One key, multi-provider access

Use Chat/Compare/Blend/Judge/Failover from one dashboard.

Evaluation criteria

Routing intelligenceLatency overheadFallback chainsCost awarenessEase of integration

LLMWise Auto RouterLLMWise

Heuristic routing that classifies queries via regex patterns and maps them to the optimal model in microseconds. No ML inference step means no added latency. If the chosen model is down, the mesh layer reroutes to a fallback automatically.

Zero routing latency - classification happens in microseconds, not millisecondsMesh mode provides automatic fallback routing when providers degradeOptimization engine analyzes historical data and recommends route changes

OpenRouter AutoOpenRouter

OpenRouter's auto mode selects from their full model catalog based on the prompt. Broad coverage but less transparent about routing logic, and you cannot customize the decision criteria.

Access to 300+ models for the router to choose fromSimple - just set model to 'auto' in the API callNo infrastructure to manage

Unify AIUnify

Benchmark-driven routing that uses public LLM benchmark scores to match queries to models. Good for teams that want transparent, data-backed routing decisions.

Routes based on published benchmark performanceTransparent routing logic you can inspectSupports custom routing policies

Portkey RoutingPortkey

Conditional routing with weight-based traffic splitting. Best for teams that want manual control over which requests go where, with A/B testing built in.

Weight-based traffic splitting for A/B testingConditional routing based on request metadataRetry and fallback chains configurable per route

Evidence snapshot

LLM Router: Intelligent Model Selection for Every Request scoring method

Ranking evidence from practical criteria teams use for real production traffic.

Criteria

evaluation dimensions used

Models ranked

candidates evaluated

Top pick

LLMWise Auto Router

current #1 recommendation

FAQ coverage

selection objections addressed

Our recommendation

For most teams, LLMWise's auto-router is the best starting point - it adds zero latency and handles 90%+ of routing decisions correctly out of the box. If you need to customize routing based on benchmarks, Unify AI gives you more transparency. For manual traffic splitting and A/B testing, Portkey offers the most control.

Use LLMWise Compare mode to verify these rankings on your own prompts.

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Common questions

What is LLM routing?

LLM routing is the practice of directing each API request to the best-fit model based on task type, cost constraints, and latency requirements. Instead of hard-coding GPT-5 for everything, a router classifies each query and sends it to the model that best matches - sending simple tasks to cheap models and complex tasks to expensive ones.

Does LLM routing add latency?

It depends on the implementation. ML-based routers add 50-200ms for classification inference. LLMWise uses regex-based heuristic classification that runs in microseconds - effectively zero added latency. The time saved by picking the right model often outweighs any routing overhead.

How is LLM routing different from an LLM gateway?

A gateway provides the infrastructure layer - unified API, authentication, failover. A router adds the intelligence layer - deciding which model handles each request. LLMWise combines both: the gateway handles connectivity and the auto-router handles model selection.

Can I route based on cost?

Yes. Cost-based routing sends requests to the cheapest model that meets a minimum quality threshold. LLMWise's auto-router does this by default - simple queries like classification or extraction go to cheaper models while complex reasoning tasks go to frontier models.

One wallet, enterprise AI controls built in

Credit-based pay-per-use with token-settled billing. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

Chat, Compare, Blend, Judge, MeshPolicy routing + replay labFailover without extra subscriptions

Start free with 20 credits See pricing examples

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