Hilde · Decision models · answer key v2

Decision model

Jev 1.14.0

1 question per request

59.2% of the 2,198 questions right (57.1% to 61.2%, 95% interval). Back to the leaderboard.

How we called it

Kind
Decision model
Access
TypeSafe System One API
Paid as
Provider service
Model ID
jev-1.14.0
Confidence from
Option score
Run
194, 16 October 2026

Settings

Reasoning
off
Request format
1 question per request
Requests at once
1
Temperature
not recorded
Harness seed
0
Harness commit
5056b43e3a36
Prompt version
254597b8be16

Results

QuestionsAccuracy95% intervalRight
All questions59.2%57.1% to 61.2%1,301 of 2,198
Reading85.1%82.1% to 87.6%558 of 656
Grammar48.2%45.7% to 50.7%743 of 1,542

Comparison group: wxyzA. Compare with another setup.

Accuracy by topic
TopicPartAccuracyRight
Word and phrase meaningsReading79.4%104 of 131
Sentence meaningsReading89.6%138 of 154
How a writer explains and develops ideasReading74.3%52 of 70
Topic and main point of a paragraphReading94.9%93 of 98
How a paragraph fits togetherReading77.4%82 of 106
Details that support a paragraph’s main pointReading91.8%89 of 97
Word types, such as nouns and verbsGrammar55.7%78 of 140
Groups of words built around a nounGrammar47.7%31 of 65
Verbs and their formsGrammar58.2%53 of 91
Verb forms used like nouns or modifiersGrammar52.8%38 of 72
Word endings and what they doGrammar48.1%38 of 79
How words are builtGrammar34.8%24 of 69
The roles of words and phrases in a sentenceGrammar45.5%66 of 145
How verbs show who acts and who receives the actionGrammar58.1%43 of 74
Types of sentencesGrammar50.6%43 of 85
Questions combining several grammar topicsGrammar36.8%81 of 220
Sound patterns and changesGrammar33.8%26 of 77
SpellingGrammar41.4%55 of 133
PunctuationGrammar51.3%60 of 117
Problems in sentence wordingGrammar61.1%107 of 175

Page images (preliminary)

Preliminary: these numbers are not final and may change. This setup is condition A of the Page images tab, which asks the 763 questions with underlined or numbered words as text (A), as a page image (B), as both (C) and through OCR models (D); the share answered right, with its 95% interval.

ModelA · text onlyaccuracy, higher is betterB · image onlyaccuracy, higher is betterC · text plus imageaccuracy, higher is betterBest OCR routeaccuracy, higher is better
Jev 1.14.01 question per request54.3%50.7% to 57.8%43.3%39.8% to 46.8%58.6%55.1% to 62.0%46.4%via Surya OCR 242.9% to 49.9%

Confidence

Answers kept at 99% or more
260, of which 1 wrong (share right: 97.9% to 99.9%, 95% interval); 1,938 skipped, the model less than 99% sure
Calibration gap
2.5 points
AUROC, all questions
0.79 0.77 to 0.81
AUROC, reading
0.88 0.85 to 0.91
AUROC, grammar
0.70 0.67 to 0.72
Brier score
0.180
Accuracy of its surest answers
most confident fifth: 98.6% right; most confident half: 81.3% right; most confident four fifths: 66.0% right
Typical score of a right answer
76.0%
Typical score of a wrong answer
41.0%

Repeats

Run 5 times on all questions.

Answers changed in 5 runs
291 of 2,198
Same wrong answer in all 5
719 of 2,198
Wrong in at least one run
1,010 of 2,198
Accuracy in each run
59.2%, 58.2%, 58.8%, 57.8%, 58.3%

Latency

Latency, median request
0.211 s (this run)
Latency, 90th percentile
0.277 s
Requests at once
1
Throughput
265.7 questions per minute of request time
Request time
8.3 minutes, over the requests whose answers were kept

Latency: the time from sending one request to receiving its answer, measured from our computer, network and any retries within the request included. Request time: the time at least one request was in flight, over the requests whose answers were kept. It is not the run's elapsed time: it leaves out requests that failed and any pause before a run was resumed.

Cost

$ per 1,000 questions
$0.029
Whole run
$0.063
Basis
Estimated from published prices and recorded token usage
Price
$0.042 input, output free per 1M tokens (source, 2026-10-16)
Input tokens per question
687
Output tokens per question
52

Going first in front of an LLM

Replay of recorded answers, cutoff chosen on half the questions, averaged over the splits. Savings are estimates from API prices; the Method page explains how.

LLM behind itShare takenAccuracy changeSaving
Gemini 3.8 Flashhigh reasoning · 16 questions per request11.8%−0.09 points11%
GPT-6 Astrahigh reasoning · 16 questions per request11.8%−0.09 points11%
GPT-6.1 Solhigh reasoning · 16 questions per request11.8%−0.09 points10%
GPT-6 Astralow reasoning · 16 questions per request11.8%−0.09 points11%
GPT-6 Astralow reasoning · 1 question per request11.8%−0.09 points12%
Gemini 3.8 Flashlow reasoning · 1 question per request13.6%−0.13 points11%
GPT-6.1 Sollow reasoning · 1 question per request13.7%−0.13 points13%
GPT-6.1 Sollow reasoning · 16 questions per request11.8%−0.09 points9%
Claude Opus 5.5high reasoning · 16 questions per request14.5%−0.14 points14%
GPT-6.1 Terrahigh reasoning · 16 questions per request12.0%−0.10 points6%
Claude Opus 5.5low reasoning · 1 question per request13.4%−0.11 points13%
Gemini 3.8 Flashlow reasoning · 16 questions per request15.5%−0.14 points5%
GPT-6.1 Terralow reasoning · 16 questions per request14.3%−0.17 points7%
Claude Opus 5.5low reasoning · 16 questions per request15.9%−0.15 points15%
Claude Sonnet 5.5high reasoning · 1 question per request12.4%−0.12 points12%
Claude Sonnet 5.5high reasoning · 16 questions per request29.2%−0.12 points28%