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DecisionNodeDecisionNde
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api all systems normal

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  • dnModelTyped answers, calibrated confidence
  • msInferenceOur own stack and GPUs, answers in ms
  • %BenchmarksAccuracy per suite, with intervals
  • exExamplesBuilds you can start from today
  • /v1DocsQuickstart, API reference, recipes
  • $PricingPay per input token, output is free
playgroundmock responsesDeterministic mock, exact API shape

Ask typed questions. Get typed answers.

Paste any text, JSON or image, ask typed questions, and get typed answers with confidence in milliseconds. Every type names its answer: choice (one of your labels), score (a level on your scale), truth (a probability), number (a value on your grid). Then copy the exact request as curl, Python or TypeScript.

endpoint
POST /v1/decide
models
DecisionNode-⁠1.0DecisionNode-⁠1.0 Flash
output tokens
0, always free
api key
none needed here
lessons, one per type
builds you could ship

State

Any text or JSON. Read once, shared by every question.

valid JSON, 6 top-level keys. Esc then Tab leaves the editor

reading...

Questions (5)

One typed answer each, from the same pass.

  • Is this statement true? One calibrated probability from 0.00 to 1.00 that the statement is true. 0.80 means true about 8 times in 10. Your code picks the cut-off: 0.50 for a plain yes or no, higher when acting on a false yes is costly.

  • returns one number from 0.00 to 1.00: the probability that the statement is true

  • returns one of your options, a probability for each, and confidence

    options, names returned exactly as written4 of 255

  • returns the expected level, a probability per level, and confidence

    levels, lowest first3 of 10
    1. 0
    2. 1
    3. 2

  • returns one number from 0.00 to 1.00: the probability that the statement is true

Add

136 input tokens, output free$5.71 per million runs like thisper 1M runs

Reading the images...

Response

mock responses

Press Run to get typed answers.

Every question comes back in the shape its type defines, with how sure the model is. Output is always 0 tokens: nothing is generated.

  • Choiceone of your options, a probability for each
  • Scorethe expected level on your scale
  • TruthIs this statement true? One calibrated probability from 0.00 to 1.00 that the statement is true. 0.80 means true about 8 times in 10. Your code picks the cut-off: 0.50 for a plain yes or no, higher when acting on a false yes is costly.
  • Numbera value on your grid, the expected value, and a probability for every value

New here? .

136 input tokens

endpoint
POST /v1/decide
models
DecisionNode-⁠1.0DecisionNode-⁠1.0 Flash
output tokens
0, always free
api key
none needed here
DecisionNodeDecisionNde

The decision model, and the inference API that serves it.

one endpoint: POST api.decisionnode.com/v1/decidePOST /v1/decide

start building

Your first decision in minutes.

Make a key, paste one curl, branch on a typed answer. Prepaid, no sales call.

  • api all systems normalapi normal
  • output is always freeoutput always free
  • same request, same answersame request, same answer

DecisionNode is built and run by Bynn Intelligence, Inc.

We train the model and serve it on our own GPUs.

hello@bynn.com

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prices in USD per 1M input tokens