Model Router
A model router dispatches every request to the most suitable model (small/large, open/proprietary, local/cloud) based on complexity, cost, latency and policy — and can combine several models.
A Model Router optimizes the allocation of requests to AI models based on factors such as complexity, cost, and latency, maximizing efficiency and performance.
Explanation
Vendors like Portkey, Martian, OpenRouter and Not Diamond established the model router as a standard layer of the enterprise AI stack in 2026.
Marketing Relevance
Without a router, teams stay locked to one vendor, cannot optimise cost and remain exposed to outages.
Example
The router sends simple classification to Gemini 3.6 Flash-Lite, complex reasoning to Claude 4.6 — transparent to the application code.
Common Pitfalls
Routers must run evals; otherwise they drift toward cheaper but weaker models.
Origin & History
Model Routers emerged between 2024 and 2026 as critical infrastructure for enterprises leveraging diverse AI models to enhance scalability and cost-efficiency of their AI applications. Key players including Google, AWS, and specialized start-ups drove development to meet the increasing demand for dynamic model orchestration.
Marketing Use Cases
Analyze customer inquiries to automatically route them to specialized language models for support or sales.
Optimize advertising campaigns by dynamically selecting the most cost-effective and performant image generation model.
Personalize user experiences on websites and apps by intelligently assigning content recommendation models.
Efficiently A/B-test different LLM models for marketing copywriting tasks through automated routing.
Frequently Asked Questions
How does a Model Router reduce an agency's operational costs?
By intelligently assigning requests to the most cost-effective model for each task, for instance, using smaller, local models for simple queries instead of expensive cloud LLMs, licensing and API costs are reduced.
What role does latency play in model selection by a Model Router?
Latency is crucial for real-time applications; the router selects models with the lowest processing time and optimal geographical proximity to ensure rapid responses for the end-user or internal processes.
Can a Model Router manage proprietary and open-source models simultaneously?
Yes, Model Routers are explicitly designed to seamlessly orchestrate a heterogeneous landscape of proprietary models (e.g., GPT-4, Claude 3) and open-source alternatives (e.g., Llama 3), depending on policy and use case.
Related Services
Go deeper: Agentic AI Hub · Governance & compliance