Comparisons· Last updated 2026-09-21

Jev versus high-precision systems: a practical comparison

A high-precision system only auto-acts when it is rarely wrong. Jev can participate if you pin a version, keep System Two work in code, and abstain aggressively. TypeSafe’s own jev-1.13 jaggedness page (reviewed 2026-09-17) is the checklist.

Unofficial EEAT page. Pointers, not a scrape of their table. Canonical: jaggedness. We do not sell keys.

Comparison scope

Precision here means your auto-action precision, not a leaderboard. Vendor workflow evals stay on their blog.

Independent angle (cover, do not clone)

Win delta (limitations-jaggedness): version-pinned jaggedness checklist + workarounds in code; honesty over hype. We do not clone a rival limitations URL.

Criteria that decide the architecture

Decision quality and control

jev-1.13 is described by TypeSafe as fast, calibrated, and good at common-sense — and weak at numeric precision and indirection. High-precision auto-act that needs those skills should not ask Jev to do them.

Integration trade-offs

Pin jev-1.13.0. Log response.model. High τ on confidence for Choice/Score; remember Noul has no confidence field. Dual-stack tests on the same JSON body.

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

• The judgment is a short common-sense call and you can abstain

Prefer High-precision systems when

• You need exact compute, multi-hop proof, or generation

Precision = Jev on what it is good at + code on what it is not + humans on the rest.

Workarounds in code (not TypeSafe defaults)

# Count in code, not in the model.
items = extract_candidates(text)  # regex / parser
res = client.system_one(
    {"items": items},
    {f"i_{n}": {"type": "noul", "instructions": f"Is items[{n}] a prohibited item per policy X?"}
     for n in range(len(items))},
)
hits = [items[n] for n in range(len(items)) if res.answers[f"i_{n}"].noul > 0.5]
# Date parts as Choice; compare in datetime.

// Do not interpolate a dollar amount from Score probabilities (official numeric warning).
if (score.confidence < abortFloor) return "review";

Full mode list: jaggedness on this site.

What this page does not claim

• No invented precision@k.

• Jaggedness will change in later versions — re-read TypeSafe.

• Schema-safe output is not the same as factual correctness.

• No independent bake-off numbers live here.

FAQ

Does pinning make Jev deterministic? It stops alias drift. It does not create bit-identical replay.

Can I reuse a Noul threshold on a Choice? Official warning: no. Different questions.

Is “can’t hallucinate” high precision? It means out-of-schema, not truth. Label that when you quote the launch post.

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: jaggedness, vs high recall systems, decision boundaries. Canonical: https://docs.typesafe.ai.