Comparisons· Last updated

Jev versus explainable models: a practical comparison

Explainable models (linear scores, GAMs, SHAP on GBMs) attribute features to a score. Jev does not publish per-token attributions in the public docs we used. Your explanation is the question pack plus probabilities you logged.

Unofficial. Not an XAI survey. docs.typesafe.ai.

Comparison scope

If a regulator wants coefficient tables, a GLM may still win. If they want “which rubric did you apply?”, Jev criteria are at least readable — that is not the same as faithful inner-model XAI.

Criteria that decide the architecture

Axis Jev (System One) Explainable models (XAI)
Feature attributions Not documented Wins
Human-readable rubric instructions + criteria Sometimes
Generated rationale None (good — no fake chain-of-thought) Some LLMs fake it
Trace You persist it You persist it

Decision quality and control

Readable criteria can still be applied wrongly. Do not treat the rubric as a proof of correctness.

Integration trade-offs

Store question version, model id, full probabilities, and the action. That is your decision trace.

TypeSafe’s public models page lists jev-1.13 at $0.042 per million input tokens with output tokens free — a vendor claim, not a jev.pro measurement. Confirm on the models page before you bid.

When each approach fits

Prefer Jev when

Prefer Explainable models (XAI) when

Use Jev where rubrics suffice; use classical XAI where features must be attributed.

What this page does not claim

FAQ

Why did it pick option B? Because you asked a Choice and B had the highest probability. There is no essay.

Can I ask Jev to explain? That would be generation. Don’t.

Disclaimer

This is an independent unofficial site and is not affiliated with TypeSafe AI; official documentation is available at https://docs.typesafe.ai. Never treat jev.pro as TypeSafe official documentation. We do not sell, issue, or proxy API keys.

Hub: Comparisons. Siblings: vs black box models, vs risk rules, glossary decision trace. Canonical: https://docs.typesafe.ai.

Sources

Public TypeSafe or adjacent documentation only. No private claims.