how much does Jev cost?

$0.042/M input, output free. you pay per run from your inference shell credits. no subscription is required.

how do I run Jev via api?

call typesafe/jev with the javascript or python sdk, the rest api, or `belt app run typesafe/jev` from a terminal. the api reference on this page lists every input.

Jev is made by typesafe and runs on inference shell. every typesafe app is listed at https://inference.sh/apps/typesafe.

can my agent use Jev?

yes. agents call it as a tool through the inference shell mcp server (https://api.inference.sh/mcp), the belt cli or the sdk, and pay per run like you do.

what are the alternatives to Jev?

other decision apps on inference shell include Decision 3.0 d3 27B, Decision 3.0 d3-flash 9B, Decision 3.0 d3-mini 4B, Decision 3.0 d3-nano 2B. they run through the same api, so switching is a one-line change.

Jev

TypeSafe's System One model. Send text and images with typed questions (choice, score, noul); get calibrated, structured answers your code can act on directly.

classification routing moderation vision

run in browser →run via API run with your agent

maker: typesafe
category: decision
runs via: api, javascript and python sdk, belt cli, mcp
updated: 2026-10-15
price: $0.042/M input, output free

api reference

about

typesafe's system one model. send text and images with typed questions (choice, score, noul); get calibrated, structured answers your code can act on directly.

get an api key

create one in settings → api keys. the examples read it from INFERENCE_API_KEY.

bash

1export INFERENCE_API_KEY="inf_your_key"

1. calling the api

install the client

nothing to install. any http client works; the examples use curl, and jq to read responses. every response wraps its result in a data field.

run and get result

send "wait": true to hold the connection until the task finishes. without it the call returns right away with the task still running.

bash

12# "wait": true holds the connection until the task finishes.3# the response is {"data": {"id", "status", "status_text", "output", ...}}4curl -X POST https://api.inference.sh/apps/run \5  -H "Authorization: Bearer $INFERENCE_API_KEY" \6  -H "Content-Type: application/json" \7  -d '{8    "app": "typesafe/jev",9    "input": {10      "state": "Our API started returning 500 errors 20 minutes ago and we can'\''t process any customer orders.",11      "choices": [12        {13          "id": "choices_1",14          "instructions": "instructions",15          "options": [16            {17              "name": "options_1"18            },19            {20              "name": "options_2"21            }22          ]23        }24      ],25      "scores": [26        {27          "id": "scores_1",28          "instructions": "instructions",29          "levels": [30            "levels_1",31            "levels_2"32          ]33        }34      ],35      "nouls": [36        {37          "id": "nouls_1",38          "instructions": "instructions"39        }40      ]41    },42    "wait": true43  }'

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks. send "stream": true and the response is a server-sent event stream that ends when the task does.

bash

12# "stream": true answers with server-sent events until the task finishes3curl -N -X POST https://api.inference.sh/apps/run \4  -H "Authorization: Bearer $INFERENCE_API_KEY" \5  -H "Content-Type: application/json" \6  -d '{7    "app": "typesafe/jev",8    "input": {9      "state": "Our API started returning 500 errors 20 minutes ago and we can'\''t process any customer orders.",10      "choices": [11        {12          "id": "choices_1",13          "instructions": "instructions",14          "options": [15            {16              "name": "options_1"17            },18            {19              "name": "options_2"20            }21          ]22        }23      ],24      "scores": [25        {26          "id": "scores_1",27          "instructions": "instructions",28          "levels": [29            "levels_1",30            "levels_2"31          ]32        }33      ],34      "nouls": [35        {36          "id": "nouls_1",37          "instructions": "instructions"38        }39      ]40    },41    "stream": true42  }'

run in the background

start the task and get its id back right away, then check on it later. for long tasks, or when you'd rather be called back, see webhooks.

bash

1# without "wait" the call returns the task right away (status 1, "received")2TASK_ID=$(curl -s -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "typesafe/jev",7    "input": {8      "state": "Our API started returning 500 errors 20 minutes ago and we can'\''t process any customer orders.",9      "choices": [10        {11          "id": "choices_1",12          "instructions": "instructions",13          "options": [14            {15              "name": "options_1"16            },17            {18              "name": "options_2"19            }20          ]21        }22      ],23      "scores": [24        {25          "id": "scores_1",26          "instructions": "instructions",27          "levels": [28            "levels_1",29            "levels_2"30          ]31        }32      ],33      "nouls": [34        {35          "id": "nouls_1",36          "instructions": "instructions"37        }38      ]39    }40  }' | jq -r '.data.id')4142# later: read its state. done when status is 10 (completed), 11 (failed) or 12 (cancelled)43curl -s https://api.inference.sh/tasks/$TASK_ID \44  -H "Authorization: Bearer $INFERENCE_API_KEY" | jq '.data | {status, status_text, output}'

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

pass urls directly or use data uris for inline content.

bash

1# pass URLs or data URIs as input values2curl -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "typesafe/jev",7    "input": {8      "image": "https://example.com/image.png",9      "audio": "data:audio/mp3;base64,..."10    },11    "wait": true12  }'

manual upload

you can also upload files manually and use the returned url.

bash

1# 1. create the file: the response has an upload_url and the file's uri2FILE=$(curl -s -X POST https://api.inference.sh/files \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{"files": [{"filename": "image.png", "content_type": "image/png"}]}')67# 2. PUT the bytes to upload_url8curl -X PUT "$(echo "$FILE" | jq -r '.data[0].upload_url')" \9  -H "Content-Type: image/png" \10  --data-binary @image.png1112# 3. pass the uri as an input value13echo "$FILE" | jq -r '.data[0].uri'

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

bash

1curl -X POST https://api.inference.sh/apps/run \2  -H "Authorization: Bearer $INFERENCE_API_KEY" \3  -H "Content-Type: application/json" \4  -d '{5    "app": "typesafe/jev",6    "input": {7        "state": "Our API started returning 500 errors 20 minutes ago and we can't process any customer orders.",8        "choices": [9            {10                "id": "choices_1",11                "instructions": "instructions",12                "options": [13                    {14                        "name": "options_1"15                    },16                    {17                        "name": "options_2"18                    }19                ]20            }21        ],22        "scores": [23            {24                "id": "scores_1",25                "instructions": "instructions",26                "levels": [27                    "levels_1",28                    "levels_2"29                ]30            }31        ],32        "nouls": [33            {34                "id": "nouls_1",35                "instructions": "instructions"36            }37        ]38    },39    "webhook": "https://your-server.com/webhook"40  }'

webhook payload

your endpoint receives a JSON POST with the task result:

json

1{2  "event": "task.completed",3  "timestamp": "2024-01-15T10:30:05Z",4  "data": {5    "id": "task_abc123",6    "short_id": "abc123",7    "status": 10,8    "status_text": "completed",9    "output": { ... },10    "created_at": "2024-01-15T10:30:00Z",11    "updated_at": "2024-01-15T10:30:05Z"12  }13}

eventstringtask.completed, task.failed or task.cancelled

timestampstringiso timestamp of the delivery

data.idstringtask id

data.short_idstringshort task id

data.statusnumberterminal status (10=completed, 11=failed, 12=cancelled, 13=rejected)

data.status_textstringthe status as a word: completed, failed or cancelled

data.outputobjecttask output (when completed)

data.errorstringerror message (when failed, omitted otherwise)

data.session_idstringsession id (when the task ran in a session, omitted otherwise)

data.created_atstringiso timestamp

data.updated_atstringiso timestamp

5. schema

input

modelstring

model name or alias: `jev-latest`, `jev-preview`, or a pinned version such as `jev-1.13.0`. pin a version if you tuned thresholds against it.

default: "jev-latest"

stateany

the content to evaluate: a string, or a json object / array of related context (messages, records, a policy). every question sees the same state. may be empty when `images` carries the content. send only what the questions need; unrelated detail costs accuracy.

default: ""example: "Our API started returning 500 errors 20 minutes ago and we can't process any customer orders."

choicesarray

choice questions: pick one option from a set.

scoresarray

score questions: place the state on ordered levels.

noulsarray

noul questions: probability that the answer is yes.

imagesarray

up to 8 images (png or jpeg, or any format pillow reads) the questions are about. sent as `{"images": [...], "text": state}`, so questions can name `images[0]`. downsized to 1568 px on the long side; one under 280 x 280 is padded. preview feature upstream: formats and accuracy may change.

output

choicesobject

choice answers by question id.

input_tokensinteger

input tokens (billed).

modelstring*

the versioned model that answered, e.g. `jev-1.13.0`.

noulsobject

noul answers by question id.

output_tokensinteger

output tokens (free upstream).

scoresobject

score answers by question id.

other decision apps

Decision 3.0 d3 27B

vllm-sr/d3

GPU time, billed per second

Decision 3.0 d3-flash 9B

vllm-sr/d3-flash

GPU time, billed per second

Decision 3.0 d3-mini 4B

vllm-sr/d3-mini

GPU time, billed per second

Decision 3.0 d3-nano 2B

vllm-sr/d3-nano

GPU time, billed per second

Decision 3.0 d3-lite 0.8B

vllm-sr/d3-lite

GPU time, billed per second

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Jev

api reference

about

get an api key

1. calling the api

install the client

run and get result

stream live updates

run in the background

2. authentication

3. files

automatic upload

manual upload

4. webhooks

5. schema

input

output

other decision apps

new models

ready to run Jev?