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System One32K context

Jev 1.13 on QuickSilver Pro

Jev 1.13 is TypeSafe's System One model. It does not write text: you send a state and a set of typed questions, and it answers each one in a single forward pass — pick one of your options, place the state on your scale, or return a yes-leaning probability — with calibrated probabilities attached. Call it on POST /v1/systemone with the same QuickSilver Pro key and USD balance as the rest of the catalog: $0.042 per million input tokens, and output tokens are free.

$0.042 per 1M input tokens · output free
ByRaullen Chai·Updated

At a glance

Context
32K tokens
Input / 1M
$0.042
Output / 1M
Free
Endpoint
/v1/systemone

Routing, classification, triage and guardrail decisions as calibrated probabilities — nothing to parse.

Pricing comparison ($/1M tokens)

ProviderInputOutputvs QSP
QuickSilver Pro$0.042Free
TypeSafe list price (jev-1.13)$0.042Freesame

When to use

Reach for Jev 1.13 wherever your code needs a decision rather than prose: routing a request to the right model or queue, classifying or triaging tickets, scoring content against a rubric, moderation and guardrail checks, or choosing an agent's next step. Every answer comes back typed — a choice with a probability per option and a confidence, a score, or a probability — so there is no free text to parse and no JSON to repair, and you can threshold on the probability instead of trusting a bare label. Up to 64 questions can share one state in a single call, and because only input is billed, a decision over a 1,000-token state costs about $0.00004.

When to use something else

Jev 1.13 does not generate text — no answers, summaries, code or tool calls — and it cannot be reached through Chat Completions; use a chat model for anything generative. Its window is 32K tokens, so trim or summarise long documents before asking about them. Responses are not streamed and a call typically takes about 2–3 seconds end to end, so for tight loops put several questions into one request instead of making many calls.

Quickstart: POST /v1/systemone (curl)

curl https://api.quicksilverpro.io/v1/systemone \
  -H "Authorization: Bearer $QSP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "jev-1.13",
    "state": "hi",
    "questions": {
      "greeting": {
        "type": "choice",
        "instructions": "Is the state a greeting?",
        "criteria": {"yes": "it is a greeting", "no": "it is not a greeting"}
      }
    }
  }'

# {"id":"so-45a870bb532d4a72b41404cc8911c72e","model":"jev-1.13",
#  "answers":{"greeting":{"type":"choice","choice":"yes",
#    "probabilities":{"no":0.07,"yes":0.93},"confidence":0.87}},
#  "usage":{"input_tokens":314,"output_tokens":33,"cost":...,"currency":"USD"}}
python (requests)
import os, requests

resp = requests.post(
    "https://api.quicksilverpro.io/v1/systemone",
    headers={"Authorization": f"Bearer {os.environ['QSP_KEY']}"},
    json={
        "model": "jev-1.13",
        "state": {"ticket": "I was charged twice for my subscription this month."},
        "questions": {
            "queue": {
                "type": "choice",
                "instructions": "Which team should handle this ticket?",
                "criteria": {
                    "billing": "payments, charges, refunds, invoices",
                    "technical": "bugs, errors, integrations",
                    "account": "login, email, profile changes",
                },
            },
            "urgent": {
                "type": "noul",
                "instructions": "Does this ticket need a reply within the hour?",
            },
        },
    },
    timeout=30,
)
resp.raise_for_status()
data = resp.json()
queue = data["answers"]["queue"]
print(queue["choice"], queue["probabilities"])  # picked queue + per-option probabilities
print(data["answers"]["urgent"]["noul"])        # probability-like number
print(data["usage"])                              # input_tokens, output_tokens, cost

System One API, not Chat Completions: send a state and typed questions, get typed answers with probabilities. Same key and balance as every other model. Full System One docs →

FAQ

A model that makes decisions instead of writing text. You send a state — any JSON, a string or an object — plus a set of typed questions, and Jev 1.13 answers every question in one forward pass with calibrated probabilities. There are three question types: choice (pick one of the options you name, with a probability for each), score (place the state on a scale you describe) and noul (a probability-like number for a yes-leaning question).

POST https://api.quicksilverpro.io/v1/systemone with your QuickSilver Pro key as a Bearer token and a JSON body holding model, state and questions — up to 64 questions per call. It is a plain HTTPS JSON endpoint, so curl, requests or httpx all work. It is not part of the OpenAI Chat Completions surface: a chat call to jev-1.13 is rejected, and streaming is not supported. The /docs/systemone guide has the full schema, all three question types and error codes.

Input tokens only, at $0.042 per million — output tokens are free. Each response's usage block reports input_tokens, output_tokens and the USD cost of that call, deducted from the same prepaid balance as every other model. That is TypeSafe's own list rate; QuickSilver Pro adds no markup.

Answers are keyed by the question IDs you chose. A choice question returns the picked option, a probability for every option and a confidence — for example {"type":"choice","choice":"yes","probabilities":{"no":0.07,"yes":0.93},"confidence":0.87}. A noul question returns a single number, such as {"type":"noul","noul":0.69}. The response also carries an id, the model and a usage block with the call's cost.

Try Jev 1.13 with double credits — up to $50 in bonus credits

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