New in llama.cpp: Decision Models
New in llama.cpp: Decision Models
Published October 2, 2026
- +47
llama.cpp server now supports decision models through the `/v1/systemone` endpoint. You send a state (text, JSON, a screenshot) and typed questions. The model returns a probability for each option in a single forward pass.
The API follows the System One format introduced with TypeSafe's Jev model, so existing clients only need a new base URL. Implementation details are in PR #29818.
What is a decision model? A model that answers by scoring the options you give it, instead of generating text. A chat model spends one forward pass per output token, and its output still has to be parsed. A decision model reads the input once, and its answer is always one of your options, with a probability attached. Typical uses are routing a request, moderating content, checking that an agent's step worked, or choosing its next action.
Supported models
| Model | Size | Based on | Languages | Images | License | Speed\* | | ------------------------------------------------------- | ---- | ---------------- | ---------------------- | ------ | ------------ | ------- | | Julia-1 | 144M | mmBERT-small | 50+ | no | Apache 2.0 | 3 ms | | Laya | 421M | ModernBERT-large | English | no | Apache 2.0 | 5 ms | | Kev-4B | 4B | Qwen3.5-4B-Base | English | no | Apache 2.0 | 12 ms | | lev | 4B | Qwen3.5-4B | English | no | Apache 2.0 | 36 ms | | OpenJev | 27B | Qwen3.8-27B | en, de, fr, hi, zh, ja | yes | CC BY-NC 4.0 | 43 ms |
\*Median time to answer one question, on one NVIDIA RTX PRO 6000.
Find these models in the Decision models collection, with more coming. The community Decision Index shows how they compare.
Quick start
Get the latest llama.cpp from llama.app (or run `llama update`), then start a model:
llama serve -hf ggml-org/Kev-4B-GGUFA request contains a state and one or more questions. There are three question types:
| Type | You send | You get | | ------ | ----------------------------------- | --------------------------------------------- | | choice | options, with optional descriptions | the top option, plus a probability per option | | score | 2 to 10 levels, lowest first | the expected level (can fall between two) | | noul | a yes/no question | the probability of yes |
Send a request with your state and questions:
curl http://localhost:8080/v1/systemone \
-H "Content-Type: application/json" \
-d '{
"state": "Customer message: I was charged twice for my order last week and nobody has replied.",
"questions": {
"route": {
"type": "choice",
"instructions": "Which team should handle this?",
"criteria": {
"billing": "payments, charges, refunds, invoices",
"shipping": "delivery, tracking, lost or late parcels",
"technical": "bugs, errors, login problems"
}
},
"angry": {
"type": "noul",
"instructions": "Is the customer angry?"
},
"urgency": {
"type": "score",
"instructions": "How urgent is this?",
"criteria": ["can wait", "this week", "today", "right now"]
}
}
}'Response (values rounded):
{
"model": "ggml-org/Kev-4B-GGUF",
"answers": {
"route": {
"type": "choice",
"choice": "billing",
"probabilities": {"billing": 0.9049, "shipping": 0.0275, "technical": 0.0676},
"confidence": 0.8574
},
"angry": {
"type": "noul",
"noul": 0.8208
},
"urgency": {
"type": "score",
"score": 2.2821,
"legend": {"0": "can wait", "1": "this week", "2": "today", "3": "right now"},
"probabilities": {"0": 0.036, "1": 0.1937, "2": 0.2225, "3": 0.5478},
"confidence": 0.2821
}
},
"usage": {"input_tokens": 130, "output_tokens": 0}
}The full reference is in the server docs.
Images
Some models (OpenJev at the time of writing) can also read images, such as documents or screenshots. The vision projector downloads automatically:
llama serve -hf ggml-org/OpenJev-GGUFFor example, to classify an uploaded document:
import base64
import requestswith open("document.png", "rb") as f:
image = "data:image/png;base64," + base64.b64encode(f.read()).decode()
response = requests.post("http://localhost:8080/v1/systemone", json={
"state": "A file uploaded by a customer.",
"images": [image],
"questions": {
"kind": {
"type": "choice",
"instructions": "What kind of document is this?",
"criteria": {"invoice": None, "receipt": None, "contract": None, "other": None},
},
},
})
print(response.json()["answers"]["kind"]["choice"]) # invoice
The `state` can also be a list of chat messages. Any `image_url` part (data URL) is read as an image, same as chat completions.
Several models, one server
In router mode, models load on demand and you pick one per request:
llama serve
curl http://localhost:8080/v1/systemone \
-H "Content-Type: application/json" \
-d '{"model": "ggml-org/Julia-1-GGUF:Q8_0", "state": "...", "questions": {...}}'`/v1/models` lists the ids. With a single model loaded, the `model` field is ignored.
Tips
What's next
New open decision models come out every week, and we'll keep adding the best ones. Cloudflare's Clef is next. Is there one you particularly want? Tell us in the comments.
Models mentioned in this article 5
Collections mentioned in this article 1
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