Jev prices a decision, not a conversation — and it shows in the bill
TypeSafe AI's Jev is a "System One" model: it skips text generation and returns a typed decision in one pass. On the routing/classify/score work it's built for, that architecture undercuts frontier LLM pricing by 1–2 orders of magnitude.
$0.042/M in
Jev input tokens — output is free
~76–209×
cheaper per decision than GPT‑5.6 Terra / Sol
70–500ms
latency, vs 3–329s for frontier LLMs on the same task
Cost to run 1,000 structured decisions
TypeSafe AI internal eval · bars to true scale
$0.40
Jev
TypeSafe AI
$30.40
GPT‑5.6 Terra
OpenAI
$83.60
GPT‑5.6 Sol
OpenAI
List price — input tokens, per million
published pricing, Sep 2026
JevTypeSafe AI
$0.042
Haiku 4.5Anthropic
$1.00
Gemini 3.1 ProGoogle
$2.00
Sonnet 5Anthropic
$2.00
GPT‑5.6 TerraOpenAI
$2.00
GPT‑5.6 SolOpenAI
$4.00
Opus 5Anthropic
$5.00
Fable 5.1Anthropic
$10.00
$0 → $10.00 per million input tokens
Where the comparison actually holds
Jev is cheap here
Classify, route, score, or pick from a known set of typed outcomes
High-frequency, low-latency loops — game AI, robotics, ticket routing
Single forward pass, no token-by-token generation to meter
Not what Jev does
Open-ended chat, long-form writing, or code generation
Anything needing free-text output — Jev returns structured fields only
General reasoning outside a pre-defined decision space
The per-decision figures above are TypeSafe AI's own published benchmark comparing Jev to GPT-5.6 Terra and Sol on identical decision tasks — independent, third-party evals aren't out yet. Token list prices are pulled from each vendor's published API pricing. Read the accuracy trade-off before betting a workflow on it.