JEV / SYSTEM ONE
Uses the Jev decision playground
Uses OpenRouter’s Decisions endpoint and the shared model, state and questions contract. The main decision playground sends text, JSON, image attachments and typed questions to d1-ultra.
LIQUID / OPENROUTER
Liquid d1-ultra
Liquid AI’s largest System One decision model takes shared text, JSON or images and returns Choice, Score or Noul answers with probabilities.
liquid/d1-ultraTextJSONImages
New accounts get 100 credits. The playground and API share one balance.
Context window
32,768
tokens · provider-listed maximum
OpenRouter input price
$0.042 / 1M
per million input tokens
OpenRouter output price
$0 / 1M
output tokens are free upstream
This site's input rate
600
credits per million input tokens · minimum 1 per successful request
SPAN / NOUL
How it differs from Span
Span-01 and Span-01 Lite accept only Noul behavior questions and require text or a specific input/output conversation object. General decision models also accept Choice and Score questions with text, JSON objects or arrays as state. Span-02 follows this broader decision contract and supports images in the shared decision playground.
Three structured answer types
Choice returns a named option and its probability distribution. Score returns a value on an ordered scale with probabilities. Noul returns the probability of a yes/no condition. Multiple questions share the same state.
choicescorenoul
OpenRouter lists a 32,768-token context. This service accepts up to 8 questions, 2–255 Choice options and 2–10 ordered Score levels. Text plus questions must fit 32 KiB. Add up to 4 PNG, JPEG or WebP images: 4 MiB and 16 MP each, 8 MiB total, and 13 MiB for the complete request.
OpenRouter describes d1-ultra as Liquid AI’s largest System One endpoint, with text and image inputs and structured Choice, Score and yes/no answers. This page follows the published listing; no live compatibility probe or accuracy benchmark is claimed.
Input and output credits
OpenRouter lists $0.042 per million input tokens and $0 for output. This service charges 600 credits ($0.06) per million actual input tokens, including questions and processed image tokens, rounded up per successful request with a minimum of 1 credit ($0.0001). That is a 30% inference gross margin before serving and payment costs. Output tokens add no charge; failed calls release the reservation.
max(1, ceil(input_tokens × 600 / 1,000,000))
A successful request with 1,000 input tokens costs 1 credit; 5,000 input tokens cost 3 credits. Output tokens add no charge. Failed calls release the credit reservation.
Checked October 16, 2026 against OpenRouter’s listing for price, context and text/image modalities. No live request or accuracy benchmark is claimed here.
Try d1-ultra in the decision playground
The Jev workbench below starts with this model selected. Try a recipe, edit the state and questions, or export API code. This page stores its browser draft separately from other model pages and the main playground.
What do you want to decide?
Choose a task to load its input and rules. Loading examples uses no credits.
Maximum credit budget: 1 credits
We reserve this budget before the model runs, then charge actual usage and return the difference. Failed calls are refunded.
New account? Receive 100 credits once. Short requests typically use 1 credit; longer inputs can use more.
100 welcome credits · one balance for web & API
Draft saved in this browser · Your draft will be restored after sign-in.
Your current configuration stays in this browser tab for the setup flow.
ILLUSTRATIVE EXAMPLE · NO CREDITS USED
“I was charged twice this morning. Please refund the duplicate payment today.”
One input → structured decisions
Choice
Billing
Route to the billing queue
Yes / no
96%
Probability of an urgent request
Score
2.8 / 3
Urgency on a 0–3 scale
Static illustration of the output format. Values are not a live model response or a measure of accuracy.
Test the same cases against two rule sets
Capture A, change the model or questions in the workbench, then capture B. Both versions use identical states.
Capture A from the current workbench model and rules. Change the model or questions, then capture B. Import up to 25 labeled cases and compare both versions. The dataset state replaces each captured state.
This simulates a policy, not accuracy. Noul uses max(P(yes), P(no)); Choice and Score use your selected signal. Validate thresholds on labeled cases.
Maximum credit budget: — credits
Total budget across both versions and all cases. Each request reserves its own allowance, then settles actual usage and refunds the remainder. Stopping preserves charges for completed requests.
New account? Receive 100 credits once. Short requests typically use 1 credit; longer inputs can use more.
Each successful comparison request uses credits. Review the total budget before starting. Requests run sequentially; stopping keeps charges for completed requests. Export includes rules, cases, results and errors. Closing this page stops the comparison.
Web runs and saved configurations are private to your account. API history stores usage only. Embedded image pixels are omitted from drafts, configurations and history; metadata and missing-image counts remain. Add the images again before replaying. API URL references may expire. API setup exports local-file code without storing pixels.Usage ↗
Use the same decision API
Send model, state, and questions to Decisions API's /v1/systemone endpoint with an API key created here. Set model to liquid/d1-ultra; answers are in data.result.answers and token usage is in data.result.usage.
// Server-side JavaScript (Node 20+ or Bun). Set DECISIONS_API_KEY.
const response = await fetch("https://decisions-api.dev/v1/systemone", {
method: "POST",
headers: {
"Authorization": `Bearer ${process.env.DECISIONS_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "liquid/d1-ultra",
"state": "I was charged twice for order A-4471. Please refund the duplicate payment.",
"questions": {
"route": {
"type": "choice",
"instructions": "Which team should handle this ticket? Use other when no option fits.",
"criteria": {
"billing": "Payments, charges and refunds",
"technical": "Bugs and product errors",
"account": "Login and account access",
"other": "None of these teams"
}
}
}
}),
});
const body = await response.json();
if (!response.ok || body.code !== 0) throw new Error(body.message);
console.log(body.data.result.answers);
console.log(body.data.creditsUsed);