If you’re using an LLM to route support tickets or classify content, Cloudflare’s Clef looks worth testing

Clef is a 27B decision model. You provide the current state, typed questions and the allowed answers. It returns probabilities for those answers in one pass, so there’s no generated text to parse.

The weights are available under Apache 2.0, and it runs on Workers AI: blog.cloudflare.com/clef-decision-models

In Cloudflare’s domain-classification test, Clef took 2.2 seconds compared with 4.7 seconds for gpt-oss-120b.
Model card: huggingface.co/Cloudflare/clef

What interests me is the fit for everyday backend work. Ticket routing, triage and moderation often involve choosing from a fixed set of options. Generating a text response adds work when all you need is a category.

A model built for those decisions could reduce latency and simplify testing. Whether it saves money will depend on how you run it.

If you already use an LLM for routing, try Clef on 200 of your own labelled cases. Compare accuracy, latency and cost with your current setup. Check the mistakes too, especially cases where it assigns a high probability to the wrong answer.

Here’s where I think this could go:
12 months: Decision models become a normal step in automated workflows.
24 months: Most routing calls no longer need a large general-purpose LLM.
36 months: The big labs offer their own decision models.

I could be wrong. These are Cloudflare’s benchmarks, and Clef trails Jev on some of them. Results on your own data matter more.

Where are you using an LLM just to pick from a fixed list?