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  • QuickstartGet startedGet an API key, send one request with three questions, and branch your code on the typed answers. Plain HTTPS, no SDK to install.
  • POST /v1/decideAPI referenceAnswer typed questions about a state, optional images and video frames. One request, one buffered JSON response, one answer per question.
  • QuestionsConceptsQuestions say what to decide. Each one has a type that fixes the shape of its answer: a choice from your options, a score on your scale, a…
  • ConfidenceConceptsProbabilities are calibrated per question type, so a threshold means what it says on the data we measure.
  • ImagesConceptsSend up to 16 images and text in the same request. The model reads printed and handwritten text, amounts, dates, objects and layout, and…
  • Batch jobsPatternsSend up to 10,000 requests in one file and collect the answers later, at a lower price than live calls.
  • Pricing and billingYou pay for input tokens only. Output is free because the model generates no text.
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DecisionNodeDecisionNde

Get started

  • Introduction
  • Quickstart
  • Playground
  • Console and keys
  • With coding agents
  • MCP server
  • Examples

Concepts

  • State
  • Questions
  • Choice
  • Score
  • Truth
  • Number
  • Points and boxes
  • Images
  • Video
  • Boosters
  • Confidence
  • Determinism

Models

  • DecisionNode-1.0
  • DecisionNode-1.0 Flash
  • Limits
  • Versions
  • Dedicated capacity

Fine-tuning

  • Overview
  • Prepare your dataset
  • Upload and validation
  • Start a training run
  • Watch a run
  • The quality gate
  • Use your model
  • Limits and pricing

Patterns

  • Confidence-gated routing
  • Fan-out
  • Guardrails
  • Control loops
  • Batch jobs

API reference

  • Overview
  • POST/v1/decide
  • GET/v1/models
  • POST/v1/uploads
  • Errors
  • Safety check
  • Rate limits

Sessions API

  • Sessions overview
  • POSTOpen a session
  • WSStream frames
  • DELEnd a session

Batch API

  • The batch object
  • POSTCreate a batch
  • POSTAdd requests
  • POSTFinalize a batch
  • GETRetrieve a batch
  • GETGet batch results
  • POSTCancel a batch
  • GETList batches

Pricing and billing

  • Pricing and billing
  • Refer & earn

Policies

  • Responsible use
  • Data and privacy
  • Benchmarks
  • Pricing
  • Playground
Get API key
  • Guides
  • API reference
  • Examples
  • Playground

Get started

  • Introduction
  • Quickstart
  • Playground
  • Console and keys
  • With coding agents
  • MCP server
  • Examples

Concepts

  • State
  • Questions
  • Choice
  • Score
  • Truth
  • Number
  • Points and boxes
  • Images
  • Video
  • Boosters
  • Confidence
  • Determinism

Models

  • DecisionNode-1.0
  • DecisionNode-1.0 Flash
  • Limits
  • Versions
  • Dedicated capacity

Fine-tuning

  • Overview
  • Prepare your dataset
  • Upload and validation
  • Start a training run
  • Watch a run
  • The quality gate
  • Use your model
  • Limits and pricing

Patterns

  • Confidence-gated routing
  • Fan-out
  • Guardrails
  • Control loops
  • Batch jobs

API reference

  • Overview
  • POST/v1/decide
  • GET/v1/models
  • POST/v1/uploads
  • Errors
  • Safety check
  • Rate limits

Sessions API

  • Sessions overview
  • POSTOpen a session
  • WSStream frames
  • DELEnd a session

Batch API

  • The batch object
  • POSTCreate a batch
  • POSTAdd requests
  • POSTFinalize a batch
  • GETRetrieve a batch
  • GETGet batch results
  • POSTCancel a batch
  • GETList batches

Pricing and billing

  • Pricing and billing
  • Refer & earn

Policies

  • Responsible use
  • Data and privacy
  1. docs
  2. /
  3. Get started

Fine-tuning limits and pricing

A training run costs 3 × its compute time + $50, charged when it ends: $50 only when the gate says no_gain, the compute so far when you cancel, nothing when it fails. A fine-tuned model's requests cost the base's price + $0.02 per million input tokens. No storage fee.

  • A run that ends ready

    Price
    3 × the compute time at its price + $50
  • A run that ends no_gain

    Price
    $50
  • A run that ends failed or refused

    Price
    Nothing
  • A run you cancel, or whose model you delete while it runs

    Price
    3 × the compute used so far, without the $50; nothing if it had not started
  • Requests to a DecisionNode-⁠1.0 fine-tune

    Price
    $0.062 per million input tokens: $0.042 (proposed) + $0.02
  • Requests to a DecisionNode-⁠1.0 Flash fine-tune

    Price
    $0.055 per million input tokens: $0.035 (proposed) + $0.02
  • Output, storage, deploying

    Price
    Free
What fine-tuning costs
ItemPrice
A run that ends ready3 × the compute time at its price + $50
A run that ends no_gain$50
A run that ends failed or refusedNothing
A run you cancel, or whose model you delete while it runs3 × the compute used so far, without the $50; nothing if it had not started
Requests to a DecisionNode-⁠1.0 fine-tune$0.062 per million input tokens: $0.042 (proposed) + $0.02
Requests to a DecisionNode-⁠1.0 Flash fine-tune$0.055 per million input tokens: $0.035 (proposed) + $0.02
Output, storage, deployingFree
  • The console shows the estimate before you start, from the dataset's size and the base. The charge is made when the run ends, from the time it took.
  • The balance must cover the estimate to start a run; below it the run does not start. The fee is drawn when the run ends.
  • Everything is drawn from the prepaid balance, like requests. See Pricing and billing.

A worked example#

A run whose compute costs $0.70 at its price is charged 3 × $0.70 + $50 = $52.10 if it ends ready, $50 if it ends no_gain, and nothing if it fails. Serving it on DecisionNode-⁠1.0 Flash, a million requests of 118 input tokens each (118 million tokens) cost $2.36 more than on the base.

Limits#

  • Records per dataset

    Value
    200 to 50,000
  • Dataset file

    Value
    Up to 64 MiB of JSON Lines; images are uploads, counted apart
  • Images per record

    Value
    Up to 16, as a live upload_id or inline data; not by url
  • Record weight

    Value
    0.1 to 10, default 1
  • Calibration and held-out splits

    Value
    10% of the records each, at least 50
  • Question types

    Value
    choice, score, truth, number; point and box are not trained
  • Model name

    Value
    3 to 40 of a-z, 0-9, -; unique in the workspace
  • Description

    Value
    Up to 200 characters
  • Fine-tuned models per workspace

    Value
    10
  • Versions deployed at once

    Value
    3
  • Versions kept per model

    Value
    5; older ones are archived
  • Runs at a time per workspace

    Value
    1
  • Longest run

    Value
    6 hours; longer is stopped, at no charge
  • Dataset retention

    Value
    30 days after its last run, unless kept
  • Requests kept for labelling

    Value
    30 days each, only while the workspace has the setting on
  • Who can train and deploy

    Value
    Owners, Admins and Developers; every member can see
Fine-tuning limits
LimitValue
Records per dataset200 to 50,000
Dataset fileUp to 64 MiB of JSON Lines; images are uploads, counted apart
Images per recordUp to 16, as a live upload_id or inline data; not by url
Record weight0.1 to 10, default 1
Calibration and held-out splits10% of the records each, at least 50
Question typeschoice, score, truth, number; point and box are not trained
Model name3 to 40 of a-z, 0-9, -; unique in the workspace
DescriptionUp to 200 characters
Fine-tuned models per workspace10
Versions deployed at once3
Versions kept per model5; older ones are archived
Runs at a time per workspace1
Longest run6 hours; longer is stopped, at no charge
Dataset retention30 days after its last run, unless kept
Requests kept for labelling30 days each, only while the workspace has the setting on
Who can train and deployOwners, Admins and Developers; every member can see

The workspace limits can be raised: write to us with what you need. The request limits of a fine-tuned model are those of its base, listed on Limits and at GET /v1/models.

nextIntroduction

DecisionNode is built and run by Bynn Intelligence, Inc.

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  1. A worked example
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