Does someone have examples of interesting stuff that has been built utilizing Jev/decision models? The way this is hyped up surely there must be some good stuff?
Not in a serious manner but I created a testing harness for a Nintendo 3DS game I'm making that uses the OpenAI Decisions API. The main advantage is the speed (~2-300ms per input) which I really need for this purpose.
I see Jev as a major step towards commoditizing current LLM paradigm. One thing would be to further optimize this particular route to work purely on CPU. This will grant an option to embed this feature into any application, from MS Office to games. The other is integrating this into agent workflow to vastly minimize token consumption.
[−]Lukas_Skywalker · 2026-10-11 Sun 06:11 UTC ·
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So, what exactly is the
> interesting stuff that has been built utilizing Jev/decision models
It would be interesting to see if a coding LLM trained for tool calling like GLM 5.3 would work well as a Jev model, or maybe even a flow where a model generates options (eg for a plan) and then uses a Jev to refine/optimize the path. Or similarly where else in a harness they’d help.
I am working on a game https://imperiaquiz.com/en that needs over 20,000 questions. I use jev to classify 'has statement' and 'can be a question' paragraphs/chunks taken from cli script to reduce token usage. Meaning, an LLM only starts work once I've chunked text and marked it as 'to be reviewed' instead of parsing the full content. This reduces tokens usage at least 10x on average
> interesting stuff that has been built utilizing Jev/decision models
in that case?
works like a charm
(not a product, so not much to share)