Clef requires Ollama 0.35.1 or later.

Clef is a 27B decision model from Cloudflare, fine-tuned from Qwen3.8-27B.

Clef also reads images. Add encoded images to the request and they’re scored jointly with the text.

It’s fully compatible with the Jev and System One APIs, so it works through Ollama’s /v1/systemone endpoint. See clef-flash for a smaller, faster variant.

ollama pull clef

Highlights

• Multimodal: Decide over text, JSON, or images — screenshots, receipts, forms, photos.
• One forward pass: Every option of every question is scored jointly in a single non-autoregressive pass.
• 64K context window: Twice the state Jev’s 32K window holds.
• Leading accuracy: Clef tops the Decision Index, Cloudflare’s leaderboard of decision models, and beats Jev on most of its suite.
• Apache 2.0 license

What you can build

API

Decision models use Ollama’s /v1/systemone endpoint, documented here. Put the text you want judged in state and your questions in questions. Ollama builds Clef’s prompt for you.

Every question has a type, instructions, and usually criteria:

confidence runs from 0 to 1 and shows how concentrated the probabilities are. It isn’t the chance that the answer is right. If two options tie, the answer follows the model’s option order, so put your preferred option first.

cURL

curl http://localhost:11434/v1/systemone -d '{
  "model": "clef",
  "state": {
    "ticket": "I was charged twice. Please refund the extra payment.",
    "attached": "A screenshot of the customer's bank statement."
  },
  "images": ["<base64-encoded image>"],
  "questions": {
    "team": {
      "type": "choice",
      "instructions": "Which team should handle this ticket?",
      "criteria": {
        "billing": "Payments and refunds",
        "technical": "Bugs and integrations",
        "other": "None of the above"
      }
    },
    "refund": {
      "type": "noul",
      "instructions": "Does the customer explicitly ask for a refund?"
    },
    "urgency": {
      "type": "score",
      "instructions": "How urgent is this ticket?",
      "criteria": ["Routine", "Soon", "Urgent"]
    }
  }
}'

{
  "model": "clef",
  "answers": {
    "team": {
      "type": "choice",
      "choice": "billing",
      "probabilities": {"billing": 0.981, "technical": 0.013, "other": 0.006},
      "confidence": 0.924
    },
    "refund": {"type": "noul", "noul": 0.996},
    "urgency": {
      "type": "score",
      "score": 0.704,
      "legend": {"0": "Routine", "1": "Soon", "2": "Urgent"},
      "probabilities": {"0": 0.451, "1": 0.353, "2": 0.196},
      "confidence": 0.071
    }
  },
  "usage": {"input_tokens": 1204, "output_tokens": 3}
}

Python

Use TypeSafe’s official Python SDK and point it at Ollama. The SDK requires an API key, but Ollama ignores it, so any value works.

pip install typesafe-sdk
export TYPESAFE_BASE_URL=http://localhost:11434
export TYPESAFE_API_KEY=ollama
export TYPESAFE_DEFAULT_MODEL=clef

from typesafe_sdk import Choice, Noul, Score, TypeSafeClient

questions = {
    "team": Choice(
        instructions="Which team should handle this ticket?",
        criteria={"billing": "Payments and refunds", "technical": "Bugs and integrations", "other": "None of the above"},
    ),
    "refund": Noul(instructions="Does the customer explicitly ask for a refund?"),
    "urgency": Score(instructions="How urgent is this ticket?", criteria=["Routine", "Soon", "Urgent"]),
}

with TypeSafeClient(timeout=120) as client:
    result = client.system_one(state={"ticket": "I was charged twice. Please refund the extra payment."}, questions=questions)

print(result.choices["team"].choice)   # billing
print(result.nouls["refund"].noul)     # 0.996
print(result.scores["urgency"].score)  # 0.70

Decision models aren’t in the Ollama CLI or the Ollama Python and JavaScript libraries yet. Use the API or the TypeSafe SDK for now.

More examples

Images. Send screenshots, receipts, or photos alongside any text state.

curl http://localhost:11434/v1/systemone -d '{
  "model": "clef",
  "state": "Classify each field of the attached receipt.",
  "images": ["<base64-encoded image>"],
  "questions": {
    "total": {"type": "noul", "instructions": "Is the receipt total legible?"},
    "category": {
      "type": "choice",
      "instructions": "What kind of purchase is this?",
      "criteria": {"meals": null, "travel": null, "office": null, "other": null}
    }
  }
}'

Tool call moderation. Check an agent’s tool call before it runs.

curl http://localhost:11434/v1/systemone -d '{
  "model": "clef",
  "state": "send_email(to=\"all-customers\", subject=\"FINAL NOTICE: account will be suspended today\")",
  "questions": {
    "harm": {"type": "noul", "instructions": "Could this tool call cause harm?"}
  }
}'

Benchmarks

Decision accuracy on four end-to-end business workflows from Typesafe Evals: