Jev vs GPT-6 Astra: cost per decision
The frontier end of the comparison. This is where TypeSafe's headline savings ratios come from, so treat them as an upper bound rather than a forecast.
| Scenario | Jev 1.13 | GPT-6 Astra | Ratio |
|---|---|---|---|
Light 10k items/day, 300-token state, 2 questions | $5.29 | $1,710 | 323x |
Production 100k items/day, 500-token state, 4 questions | $93.24 | $29,700 | 319x |
High volume 2M items/day, 300-token state, 1 question | $856.80 | $234,000 | 273x |
Monthly, 30 days. Both sides answer all questions for an item in a single call. GPT-6 Astra additionally pays for its output tokens at $50/M; Jev 1.13 has no output charge. List prices at standard tier, excluding caching and batch discounts.
Where GPT-6 Astra still wins
Astra is a general model. If accuracy on your task is the binding constraint rather than cost, measure both on your own labelled data first.
The honest caveat
This compares price, not accuracy. A model that is 100x cheaper and wrong 5% more often can easily be the more expensive choice once you price the mistakes. Jev returns a calibrated probability with every answer, so the practical move is to route the confident cases automatically and send the rest to GPT-6 Astra or a human — which makes this a routing decision rather than a replacement decision.