Target groups
Group multiple models behind one balancer so the endpoint stays stable while routing logic evolves.
The right model, automatically.
Route requests by availability with automatic failover, or by prompt intent to the model best suited for the task. Smart Balancers adapt every request without requiring changes to your application.
See routing logicMEETSMARTBALANCERS.
Balance beyond failover.
Smart Balancers group multiple AI models behind a single API endpoint. Every request is evaluated before inference and routed according to the strategy you define, whether based on availability, prompt intent, or custom policies, allowing multiple specialized models to behave like a single intelligent service.
MAKEROUTINGADAPT.
Define the logic behind every route.
Smart Balancers support different routing strategies depending on what your application needs. Use intent-based routing to send each prompt to the model best suited for the task, or ordered routing to follow a fixed priority and automatically move to the next healthy model when needed.
support-balancer
incoming request
Primary destination
Priority 1
Available
Primary route selected
Fallback destination
Priority 2
Standby
Primary destination is serving requests
BUILT TOKEEP GOING.
Resilience is part of the routing layer.
Smart Balancers add continuity to multi-model systems by automatically recovering from unavailable routes. Instead of treating failures as application errors, they become part of the normal execution flow, helping workloads remain available when individual models cannot respond.
MATCHEVERYTASK.
Let specialised models do what they do best.
Smart Balancers can interpret the intent of each prompt and direct it to the model best suited for that type of work. This lets you combine specialised models into a single system that uses the right capability for each task without exposing that decision to the application.
What Smart Balancers include
Fallback routing
Pair a primary group with a fallback group and use ordered failover between healthy destinations.
Prompt-based routing
Intent-based routing adds a router-model call, which can add latency and cost when selecting a destination from configured intents.
Route priorities
Ordered mode provides deterministic failover by trying healthy destinations in priority order.
OpenAI-compatible endpoint
Keep existing SDK flows and point them at one balancer endpoint instead of one raw model endpoint.
Capacity pricing inheritance
Compute-backed routes retain capacity pricing; Public Model routes use metered inference pricing at published rates.
Python
from openai import OpenAI
client = OpenAI(
base_url="https://api.qdiv0.com/v1",
api_key="your-api-key",
)
response = client.chat.completions.create(
model="support-balancer",
messages=[{"role": "user", "content": prompt}],
)Integrate once.Route forever.
Introduce routing logic without touching your client code.
Call a single Smart Balancer endpoint just as you would any model. Configure routing, intent matching, and failover behind it while your application code stays unchanged.
