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A leadership team asked a simple question: "If we build on one model provider, what happens when pricing changes or there's an outage?" They weren't being theoretical. They'd already lived through a vendor incident where a critical workflow stalled for hours.
The answer isn't "pick the best model." The answer is architecture: a router that selects the right model for each request based on complexity, cost, privacy and latency.
fast / balanced / reasoning / private
providers for resilience
of traffic on fast tier (typical)
A multi-model strategy is an approach where your application uses multiple LLMs and chooses between them at runtime. The selection is made by a router: a policy layer that routes requests based on what matters to the business (cost, SLA, privacy, reliability), not what happens to be popular this month.
Locking into a single provider creates four kinds of risk:
Most enterprise requests aren't hard reasoning problems. They're summaries, extractions, classifications, rewriting, and grounded Q&A against your data. If you send every request to your most expensive model, you're buying premium reasoning for tasks that don't need it.
A good router starts with a fast/cheap tier and escalates only when confidence is low or stakes are high (e.g. external comms, policy, anything safety-critical). This is sometimes called a cascade.
| Option | When to Use | Trade-offs |
|---|---|---|
| Single-model (no router) | Very early prototypes, low volume, non-critical use | Higher long-term cost, no resilience, limited privacy controls |
| Static routing (rules-based) | You can classify requests (task type, PII, SLA) with simple rules | Rules drift; misroutes happen; must be monitored and tested |
| Dynamic routing (confidence + eval-driven) | You want cheap-first with escalation based on quality signals | Requires evals, logging, and an operating cadence |
Define tiers: fast, balanced, reasoning, and a private tier for sensitive workloads.
If you skip the private tier, teams will block AI adoption for sensitive workflows.
Create a routing policy: PII rules, latency SLAs, and escalation criteria.
If the policy is undocumented, routing becomes tribal knowledge and hard to govern.
Instrument everything: model chosen, latency, cost estimate, fallback events, and user feedback.
Without logs you can’t prove ROI or debug misroutes.
Gate changes with evals: treat routing rules like deployments.
Routing changes can silently break quality—even if the model hasn’t changed.
A multi-model strategy is a business strategy disguised as architecture. It reduces cost, increases resilience, and gives you leverage in procurement—while letting teams use the right model for each job.
MLX includes a policy-driven multi-model router, cost analytics, and deployment options from hosted cloud to private environments.
Explore MLX →