Jev

Jev is TypeSafe's decision model. Through OpenRouter it is POST https://openrouter.ai/api/alpha/decisions with "model": "typesafe/jev-1.13". Hanzo serves the same wire at POST https://api.hanzo.ai/v1/decisions, where kai is Hanzo's decision model. The question types, their criteria and the answers are the Decisions API's on both sides, so a Jev request becomes a Kai request when three things change: the base URL, the key and model.

Start here

# 1. mint a key — a decision takes a secret key; a pk- is refused with 403
curl -sS -X POST https://api.hanzo.ai/v1/account/keys \
  -H "Authorization: Bearer $HANZO_SESSION" \
  -H 'Content-Type: application/json' \
  -d '{"type":"secret"}'

# 2. a Jev request with its base URL, key and model changed
curl -sS https://api.hanzo.ai/v1/decisions \
  -H "Authorization: Bearer $HANZO_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"model": "kai",
       "state": "The second charge on my March invoice is still pending.",
       "questions": {"is_bug": {"type": "noul", "instructions": "Is this a product defect?"}}}'

# 3. kai's row in the model catalogue, with its price; no key needed
curl -sS https://api.hanzo.ai/v1/models | jq '.data[] | select(.id == "kai")'

Step 2 needs an org whose plan covers paid models; without one it answers 402 with "code": "plan_required" and a link to pick a plan. Step 3 answers "outputs": ["decision"] and "pricing": {"input": 0.021, "output": 0}: the dollars per million input tokens every kai call is billed at.

What changes

The Jev column is OpenRouter's wire as the benchmark harness called it for 11,099 questions (three_way.py); the Kai column is what api.hanzo.ai answers.

Hanzo checks a request before any work: at most 64 questions, at most 50,000 characters of state as the model reads it, and at most 256 characters of session_id or user. A key that sends faster than its per-minute rate is answered 429 with Retry-After. The errors are listed on Decisions.

The call

Jev, on OpenRouter:

curl https://openrouter.ai/api/alpha/decisions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "typesafe/jev-1.13",
    "state": {"message": "I was charged twice for my March invoice and the second charge is still pending."},
    "questions": {
      "is_bug":  {"type": "noul", "instructions": "Is this a product defect?",
                  "criteria": {"true": "a defect", "false": "working as intended"}},
      "team":    {"type": "choice", "instructions": "Which team should handle it?",
                  "criteria": {"account": "logins and profiles",
                               "payments": "charges, invoices and refunds",
                               "product": "features and bugs"}},
      "urgency": {"type": "score", "instructions": "How urgent is it?",
                  "criteria": ["later", "this week", "today", "now"]}
    }
  }'

Kai, on Hanzo: the same body, with model changed.

curl https://api.hanzo.ai/v1/decisions \
  -H "Authorization: Bearer $HANZO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kai",
    "state": {"message": "I was charged twice for my March invoice and the second charge is still pending."},
    "questions": {
      "is_bug":  {"type": "noul", "instructions": "Is this a product defect?",
                  "criteria": {"true": "a defect", "false": "working as intended"}},
      "team":    {"type": "choice", "instructions": "Which team should handle it?",
                  "criteria": {"account": "logins and profiles",
                               "payments": "charges, invoices and refunds",
                               "product": "features and bugs"}},
      "urgency": {"type": "score", "instructions": "How urgent is it?",
                  "criteria": ["later", "this week", "today", "now"]}
    }
  }'

Kai's answer, as api.hanzo.ai returned it on 2026-09-28:

{
  "id": "dec_ed1fbe82dd2e77f85dd751dda4b08b2d",
  "model": "kai",
  "provider": "Hanzo",
  "answers": {
    "is_bug":  {"type": "noul", "noul": 0.4023, "answer_confidence": 0.5977},
    "team":    {"type": "choice", "choice": "payments", "confidence": 0.9998,
                "probabilities": {"account": 0.0, "payments": 0.9999, "product": 0.0001},
                "answer_confidence": 0.9999},
    "urgency": {"type": "score", "score": 1.7883, "confidence": 0.0797,
                "legend": {"0": "later", "1": "this week", "2": "today", "3": "now"},
                "probabilities": {"0": 0.1215, "1": 0.2687, "2": 0.3098, "3": 0.3},
                "answer_confidence": 0.3098}
  },
  "usage": {"input_tokens": 165, "output_tokens": 0},
  "routing": {
    "backend": "kai",
    "checkpoint": "a7",
    "sha256": "0834a74f2d140642a453373da09e5a128e3d2c8d9e8bb1dcaf86d7210a4ecdfc",
    "calibration": "cal_e23c27a1f768bff7",
    "device": "cpu",
    "reason": "explicit model='kai'"
  },
  "state_hash": "sha256:3893b9038056e7104d3c76ffa6f703dea7ce1d0b4bb8be153e4adbc3432b212b",
  "latency_ms": 148.752925
}

team is settled. urgency is not: no level holds more than 0.31, and its confidence is 0.0797. The call was billed its 165 input tokens: 165 × $0.021 / 1,000,000 = $0.000003465, the amount its row in GET /v1/billing/usage records.

What stays the same

• The request. model, state and questions, and the optional provider, session_id, user and trace. Kai accepts the optional four and uses none of them.
• The questions. choice, noul and score, each with type, instructions and criteria: a choice maps each label to its description, a noul may describe true and false, a score lists its levels lowest first.
• The answers. choice, noul, score, confidence, probabilities and legend, in the same shapes, under the names you gave. confidence is (n·p_max − 1)/(n − 1) on both, so a threshold carries over as arithmetic. What a threshold buys is the model's own calibration, so tune it again on your outcomes.
• usage.input_tokens and usage.output_tokens.
• Errors past the gateway: {"error": {"code", "message"}} on both.

What you gain

Half the price per input token. Kai is billed $0.021 per million input tokens and Jev $0.042, with output free on both. Each model counts tokens with its own tokenizer, and Kai counts per question: each question is read with the state beside it, so a five-question call counts its state five times. The same 800 requests, billed each way:

Jev's column is what OpenRouter billed the benchmark harness (kai-a7/scores.json); Kai's is what api.hanzo.ai metered for the same requests on 2026-09-28. One question a call costs 7.7 times less on Kai; five questions a call, 1.2 times less.

Higher accuracy on 11 of 12 suites. On the frozen harness, Kai a7 is more accurate than Jev on every suite but jailbreak, 0.920 against 0.940, and on 30 of the 51 MASSIVE languages, equal on 5 and lower on 16. Suite by suite: Kai's results. Its probabilities are less well calibrated than Jev's on four suites (expected calibration error, Kai against Jev): typed decisions 0.172 against 0.047, toxicity 0.191 against 0.177, jailbreak 0.072 against 0.047 and Banking77 0.076 against 0.073. A threshold tuned on Jev's confidence is to be tuned again.

Speed

A call to Kai through api.hanzo.ai takes longer than a call to Jev through OpenRouter. About 400 ms of each call (p50) is spent outside the model, in the network and the gateway, and five questions over a typed-decision state take 835 ms in the model, on CPU. Timed as the harness timed Jev, each call on a new connection:

Jev's column is the harness's, from kai-a7/scores.json. Kai's is api.hanzo.ai, measured from one client on 2026-09-28. AG News counts the 287 calls that were the first of their request, since a repeated request was answered in about 8 ms in the model. Typed decisions leaves out 9 calls the gateway answered 502 or 503, which were sent again.

What does not carry

A long state. Kai reads at most 1,024 tokens for each question: the question, then as much of the state as fits. The rest of the state is dropped and the call still answers; usage.input_tokens shows what was read, and a 40,000-character state was read as 1,044 tokens with its two options. An option is read up to its first 48 tokens. Jev's window is 32,000 tokens (OpenRouter). Put what decides the question first in state, or split a long document across calls.

usage.cost. Jev's answer states its price; Kai's states usage.input_tokens, billed at $0.021 per million. The org's spend is GET /v1/billing/usage, one row per call, model kai.

Self-hosting. Kai runs at api.hanzo.ai only: its weights and its runtime are not published, so it cannot be self-hosted today.

Jev's ids on Hanzo are billed per call. typesafe/jev-1.13 sent to api.hanzo.ai is forwarded to OpenRouter and billed $0.03 a call (pricing); on OpenRouter the AG News calls above cost $0.0000171 each.