GPT-6 Luna (default medium reasoning effort)v1.7 · 10 s rule

Data: JevBench v1.8.7, published 2026-11-03 · method v1.7 (10 s rule), re-scored from the recorded per-decision times

Capability 98.4 · API offering, ranked on the API leaderboard · outside the Jev-class caps (cost 3.5× Jev (v1.5 reference); latency 3.1× Jev (v1.5 reference)), below the Capability ranking

Measured 2026-10-06 on A4 ∪ P, 600 items, equated (+2.57 I / +3.35 C); round score-a4-2.

proprietary API

Base model: undisclosed

intelligence

96.9

calibration

99.9

speed

71.4

cost

38.4

Composite (secondary)

39.1 · Composite rank #32 of 48 on the API leaderboard

Cost and measurement conditions

$0.113 per 1,000 decisions (public tariff)

measured: token usage of the 6 Oct 2026 A4 u P run x tariff USD 0.1/M input, 0.5/M output (spec gpt-6-luna.json), per 1,000 decisions on the v1.6.1 common cost basis (591 of 600 items; the 9 A4 u P items outside the Jev reference's accepted input range are excluded, cost-basis-a4.json)

p50 latency: 1.9 s

none (API)

Measured latency over 600 decisions: p50 1.932 s · p95 3.765 s

5 decisions over 10 s (1 of them answered without error, counted as wrong).

A decision that takes longer than 10 seconds (measured time) counts as a wrong answer and as zero calibration for that item: each type's calibration is multiplied by the share of its decisions answered within 10 s. The limit uses the measured time (raw). The displayed adjusted time for self-hosted rows (2 × + 0.15 s) is an assumption and is not used for the limit.

JevBench v1.6.43 values (method v1.6, before the 10 s rule)

Capability 98.44 · Composite 39.16 · rank #84 on the all-systems board · #30 API

intelligence 96.88 · calibration 100.00 · speed 71.77 · cost 38.41

v1.6 speed basis (124 items): p50 1.824 s · p95 3.646 s

These figures are kept for comparison. The current figures above are re-scored under the 10 s rule from the recorded per-decision times and replace them.

Breakdowns (not part of the score)

Chance-corrected competence (0 = chance, 100 = perfect) on A4 ∪ P (600 items: 300 open + 300 sealed; fewer sealed items than the full set, so wider uncertainty). Raw values, not equated. Category cells use A4+P+L1+L2+L3; per-type/tier cells use the original basis above. Radars against Jev.

Request typeOpenSealed
choice99.299.2
noul97.193.4
score89.787.2

Capability by subject topic

Rules, policy & law98.9n=1133
Coding & software90.5n=202
Math & numbers91.9n=269
Finance & commerce95.7n=178
Support & operations98.8n=109
Everyday language99.4n=130
Safety & security99.8n=84

Use cases (TypeSafe categories)

Model routing93.0n=267
Legal & compliance99.3n=269
Customer support99.5n=156
E-commerce96.6n=88
Insurance claims95.2n=92
Risk assessment100.0n=88
Financial crime98.7n=76
Feature extraction96.7n=90
Lead generation97.7n=86
Recruiting100.0n=88
Knowledge graphs97.2n=82
LLM guardrails99.9n=82
Moderation98.4n=69
Code linting95.3n=81
Search & retrieval99.8n=84
Science99.9n=82
Advertising98.0n=85
Gaming87.9n=79
Demand forecasting100.0n=72

Cells need at least 15 answered items; † fewer than 30 (indicative only, listed below the radar in the compare view).

Previous measurement (v1.5.x, not comparable)

Capability 98.4 · composite 39.1 · cost $0.113 per 1,000 decisions (public list price)

Last measured 2026-10-06, measurement release v1.6.1. Older method and scale; the current figures above replace it.

Published source