# jev — API, Pricing & Context Window | Vivgrid

> Source: https://vivgrid.com/docs/models/jev

jev on Vivgrid: TypeSafe's System One model, returning typed, confidence-scored decisions in milliseconds instead of generated text.

`jev` is TypeSafe's **System One** model, and it does not write text. You send it the current `state` plus the `questions` you need answered, and it returns typed answers — a picked option, a score on your rubric, or a yes/no probability — each with a calibrated confidence value.

That makes it the right tool for the decisions an agent makes _around_ the model call: routing a ticket, grading a retrieval hit, deciding whether a step is done, gating a retry. Those are classification problems, and running them through a frontier chat model means paying for generated tokens and parsing prose back into a type. Jev answers in **70–500 ms**, typically 40–200× faster.

## Specifications

| Field | Value |
| --- | --- |
| Provider | TypeSafe |
| Model ID | `jev` |
| Best for | Decision |
| Available on | Decisions |
| Context window | 64,000 tokens |
| Modalities | Text |
| Tool / function calling | No |
| Knowledge cutoff | — |
| Acceleration | Global (centralized) |

## Pricing

Pricing in USD per 1M tokens.

| Input | Cached input | Output |
| --- | --- | --- |
| $0.084 | — | $0.00 |


## Question types

- **Choice** — pick one option from a map of option → rubric description
- **Score** — rate the state against an ordered array of levels, returning a continuous score plus its distribution
- **Noul** — a yes/no question, returning the probability the statement is true

A single request may carry many questions; `state` plus the longest question must fit in 32K tokens, and the whole request in 64K.

## API surfaces

The Vivgrid Console catalogs `jev` on one surface, all behind the same API key. The endpoint shown is the one the Console previews for that surface.

| Surface | Primary endpoint | Use it for |
| --- | --- | --- |
| Decisions | `/systemone` | Structured decision calls that return scores and choices instead of prose. |

## Quick start

Get an API key from the Vivgrid Console (https://console.vivgrid.com), then call `jev` directly.

```bash
curl https://api.vivgrid.com/v1/systemone \
  -H "Authorization: Bearer $VIVGRID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "jev",
    "state": "The website has been down for 2 hours and customers cannot complete purchases.",
    "questions": {
      "routing": {
        "type": "choice",
        "instructions": "Which team should handle this?",
        "criteria": {
          "billing": "Payments, invoicing, refunds",
          "technical": "Bugs, outages, integrations",
          "sales": "Pricing, upgrades, new accounts"
        }
      },
      "severity": {
        "type": "score",
        "instructions": "How severe is this issue?",
        "criteria": ["Minor", "Moderate", "Critical"]
      }
    }
  }'
```


## Ideal use cases

- Routing, triage, and intent classification in agent pipelines
- Guardrails and gating decisions between tool calls
- Scoring retrieval results or model output against a rubric
- High-volume labeling where per-call latency and cost dominate

## Related models

- [decision-1](/docs/models/decision-1) — Microsoft's decision model on the same `/systemone` API
- [gemini-3.8-flash](/docs/models/gemini-3.8-flash) — a fast general-purpose model when you need generated text
- [glm-5.3-flash](/docs/models/glm-5.3-flash) — low-cost chat completions for lightweight classification