LLM routing, explained
Two kinds of routing
| Kind | Chooses | Example |
|---|---|---|
| Provider routing | Which provider serves a named model | The same model from its maker or a cloud host, whichever is healthy and cheaper |
| Model routing | Which model answers at all | "auto" sends a short summary to a small model and a hard refactor to a large one |

From a 1906 handbook on telephone exchanges.
The practical telephone handbook and guide to the telephonic exchange, 1906. Internet Archive Book Images, no known copyright restrictions, via Wikimedia Commons.
How a router decides
Read the request.
Does it include images, tools, a JSON schema, a long context, a reasoning setting?
Filter.
Drop every model that can't do all of it, or that your rules forbid.
Order.
Healthy providers first, then by your strategy: lowest price, lowest latency, or a balance.
Keep a fallback list.
The next choices are kept in case the first one fails.
Why it saves money
Model prices differ by around a hundred times: on DigitSpace today the cheapest text models cost about $0.10 per million input tokens and the most expensive about $10. If most of your traffic is simple, sending it to a small model instead of a flagship cuts that part of the bill by an order of magnitude, while hard requests still get a strong model.
Questions
Isn't a cheaper model worse?
For hard tasks, often. Routing with a quality floor only picks among models good enough for the level you set, and named models are never swapped.
Does routing need an extra AI call?
Not on DigitSpace: the decision uses the request's features and live price and health data, without asking another model.
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