Datasetpublic

skyhong2002/taiwan-professional-exams-115-2-results

Benchmark results produced by any-to-bench. One subset here is one taker configuration — a single model at a single reasoning effort — sat against the exams in another dataset repo. Every row names the exam repo and subset it was earned against, so results from several corpora, and from several people, can live side by side. results-index.json — the catalog: one headline row per configuration results-<entry>/entry.json — that configuration's per-paper scores results-<entry>/raw/<subset>/ —… See the full description on the dataset page: https://huggingface.co/datasets/skyhong2002/taiwan-professional-exams-115-2-results.

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Dataset Card

Benchmark results produced by any-to-bench. One subset here is one taker configuration — a single model at a single reasoning effort — sat against the exams in another dataset repo. Every row names the exam repo and subset it was earned against, so results from several corpora, and from several people, can live side by side.

—results-index.json — the catalog: one headline row per configuration
—results-<entry>/entry.json — that configuration's per-paper scores
—results-<entry>/raw/<subset>/ — the byte-faithful bench.json, answer sheet and grade report behind those scores
—the viewer table — one row per graded question

Explore it as a leaderboard: https://jacoblincool.github.io/any-to-bench/results.html

python

from datasets import load_dataset
ds = load_dataset("skyhong2002/taiwan-professional-exams-115-2-results", "results-<entry>", split="test")

How to read these numbers

—Judged questions depend on the judge model, which is named per entry. Two configurations graded by different judges are not strictly comparable on their judged half; the rule-graded half is deterministic and always comparable.
—A score is one sample per paper unless the entry's repeat is above 1. The run-to-run spread of a single sample is unknown.
—Input-token counts are not comparable across backends. codex: reports cached tokens inside input_tokens; claude: reports them only under cache_read_tokens, leaving input_tokens near zero. Output tokens and wall time are the measures that mean the same thing for every taker; the raw per-phase counts are published unaltered so you can judge for yourself.
—Token counts for agentic takers are approximate, and wall time depends on how many runs shared the machine — see each entry's note.
—Percentages are over what the taker was actually asked. When two entries cover different papers, their percentages have different denominators.

Leaderboard

#	Model	Effort	Papers	Score	%	Rule-graded %	Solve output tokens	Solve s
1	`codex:gpt-5.6-sol`	xhigh	29	1585.75/2440	65.0%	99.7%	268,349	6,564
2	`codex:gpt-5.6-sol`	high	29	1577.25/2440	64.6%	99.2%	219,205	5,444
3	`codex:gpt-5.6-sol`	medium	29	1575.25/2440	64.6%	99.1%	189,303	4,797
4	`codex:gpt-5.6-sol`	low	29	1553.5/2440	63.7%	97.7%	144,846	3,700
5	`codex:gpt-5.6-luna`	xhigh	29	1541/2440	63.2%	96.9%	335,206	7,410
6	`codex:gpt-5.6-luna`	high	29	1532.5/2440	62.8%	96.4%	270,073	5,769
7	`codex:gpt-5.6-luna`	medium	29	1481.75/2440	60.7%	93.2%	170,633	3,681
8	`codex:gpt-5.6-luna`	low	29	1410.5/2440	57.8%	88.7%	99,489	2,181

codex-gpt-5.6-sol-low


Model	`codex:gpt-5.6-sol`
Effort	low
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1002-general-1`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1003-general-2`	38/90	42.2%	95.0%	0.0%
`clinical-psychologist-115-2-1004-special-1`	39/90	43.3%	97.5%	0.0%
`clinical-psychologist-115-2-1005-special-2`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1006-special-3`	39/90	43.3%	97.5%	0.0%
`counseling-and-psychotherapy-theories`	39/90	43.3%	97.5%	0.0%
`counseling-psychological-foundations`	39/90	43.3%	97.5%	0.0%
`counseling-psychotherapy-practice-and-ethics`	37/90	41.1%	92.5%	0.0%
`dietitian-0103-physiology-biochemistry`	50/50	100.0%	100.0%	–
`dietitian-0104-nutrition`	48/50	96.0%	96.0%	–
`dietitian-0105-public-health-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0106-food-hygiene-safety`	50/50	100.0%	100.0%	–
`group-counseling-and-psychotherapy`	37/90	41.1%	92.5%	0.0%
`mental-health-and-abnormal-psychology`	38/90	42.2%	95.0%	0.0%
`ordinary-general-0114-law-english`	98/100	98.0%	98.0%	–
`ordinary-general-0406-administrative-law`	100/100	100.0%	100.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	78/80	97.5%	97.5%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	77/80	96.2%	96.2%	–
`pharmacist-stage2-0405-pharmacotherapy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	50/50	100.0%	100.0%	–
`tw-moex-115100-public-health-specialist-0801`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0802`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0803`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0804`	46.25/100	46.2%	92.5%	0.0%
`tw-moex-115100-public-health-specialist-0805`	47.5/100	47.5%	95.0%	0.0%
`tw-moex-115100-public-health-specialist-0806`	50/100	50.0%	100.0%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-sol-low -o results

codex-gpt-5.6-sol-medium


Model	`codex:gpt-5.6-sol`
Effort	medium
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1002-general-1`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1003-general-2`	39/90	43.3%	97.5%	0.0%
`clinical-psychologist-115-2-1004-special-1`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1005-special-2`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1006-special-3`	40/90	44.4%	100.0%	0.0%
`counseling-and-psychotherapy-theories`	40/90	44.4%	100.0%	0.0%
`counseling-psychological-foundations`	39/90	43.3%	97.5%	0.0%
`counseling-psychotherapy-practice-and-ethics`	37/90	41.1%	92.5%	0.0%
`dietitian-0103-physiology-biochemistry`	50/50	100.0%	100.0%	–
`dietitian-0104-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0105-public-health-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0106-food-hygiene-safety`	50/50	100.0%	100.0%	–
`group-counseling-and-psychotherapy`	40/90	44.4%	100.0%	0.0%
`mental-health-and-abnormal-psychology`	39/90	43.3%	97.5%	0.0%
`ordinary-general-0114-law-english`	100/100	100.0%	100.0%	–
`ordinary-general-0406-administrative-law`	98/100	98.0%	98.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0405-pharmacotherapy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	50/50	100.0%	100.0%	–
`tw-moex-115100-public-health-specialist-0801`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0802`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0803`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0804`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0805`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0806`	50/100	50.0%	100.0%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-sol-medium -o results

codex-gpt-5.6-sol-high


Model	`codex:gpt-5.6-sol`
Effort	high
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1002-general-1`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1003-general-2`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1004-special-1`	39/90	43.3%	97.5%	0.0%
`clinical-psychologist-115-2-1005-special-2`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1006-special-3`	40/90	44.4%	100.0%	0.0%
`counseling-and-psychotherapy-theories`	40/90	44.4%	100.0%	0.0%
`counseling-psychological-foundations`	40/90	44.4%	100.0%	0.0%
`counseling-psychotherapy-practice-and-ethics`	40/90	44.4%	100.0%	0.0%
`dietitian-0103-physiology-biochemistry`	50/50	100.0%	100.0%	–
`dietitian-0104-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0105-public-health-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0106-food-hygiene-safety`	50/50	100.0%	100.0%	–
`group-counseling-and-psychotherapy`	40/90	44.4%	100.0%	0.0%
`mental-health-and-abnormal-psychology`	40/90	44.4%	100.0%	0.0%
`ordinary-general-0114-law-english`	100/100	100.0%	100.0%	–
`ordinary-general-0406-administrative-law`	100/100	100.0%	100.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0405-pharmacotherapy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	50/50	100.0%	100.0%	–
`tw-moex-115100-public-health-specialist-0801`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0802`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0803`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0804`	42.5/100	42.5%	85.0%	0.0%
`tw-moex-115100-public-health-specialist-0805`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0806`	50/100	50.0%	100.0%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-sol-high -o results

codex-gpt-5.6-sol-xhigh


Model	`codex:gpt-5.6-sol`
Effort	xhigh
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1002-general-1`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1003-general-2`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1004-special-1`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1005-special-2`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1006-special-3`	40/90	44.4%	100.0%	0.0%
`counseling-and-psychotherapy-theories`	40/90	44.4%	100.0%	0.0%
`counseling-psychological-foundations`	40/90	44.4%	100.0%	0.0%
`counseling-psychotherapy-practice-and-ethics`	40/90	44.4%	100.0%	0.0%
`dietitian-0103-physiology-biochemistry`	50/50	100.0%	100.0%	–
`dietitian-0104-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0105-public-health-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0106-food-hygiene-safety`	50/50	100.0%	100.0%	–
`group-counseling-and-psychotherapy`	40/90	44.4%	100.0%	0.0%
`mental-health-and-abnormal-psychology`	40/90	44.4%	100.0%	0.0%
`ordinary-general-0114-law-english`	100/100	100.0%	100.0%	–
`ordinary-general-0406-administrative-law`	100/100	100.0%	100.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0405-pharmacotherapy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	50/50	100.0%	100.0%	–
`tw-moex-115100-public-health-specialist-0801`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0802`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0803`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0804`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0805`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0806`	50/100	50.0%	100.0%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-sol-xhigh -o results

codex-gpt-5.6-luna-low


Model	`codex:gpt-5.6-luna`
Effort	low
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1002-general-1`	32/90	35.6%	80.0%	0.0%
`clinical-psychologist-115-2-1003-general-2`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1004-special-1`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1005-special-2`	36/90	40.0%	90.0%	0.0%
`clinical-psychologist-115-2-1006-special-3`	37/90	41.1%	92.5%	0.0%
`counseling-and-psychotherapy-theories`	35/90	38.9%	87.5%	0.0%
`counseling-psychological-foundations`	38/90	42.2%	95.0%	0.0%
`counseling-psychotherapy-practice-and-ethics`	33/90	36.7%	82.5%	0.0%
`dietitian-0103-physiology-biochemistry`	47/50	94.0%	94.0%	–
`dietitian-0104-nutrition`	48/50	96.0%	96.0%	–
`dietitian-0105-public-health-nutrition`	40/50	80.0%	80.0%	–
`dietitian-0106-food-hygiene-safety`	41/50	82.0%	82.0%	–
`group-counseling-and-psychotherapy`	35/90	38.9%	87.5%	0.0%
`mental-health-and-abnormal-psychology`	35/90	38.9%	87.5%	0.0%
`ordinary-general-0114-law-english`	88/100	88.0%	88.0%	–
`ordinary-general-0406-administrative-law`	79/100	79.0%	79.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	73/80	91.2%	91.2%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	67/80	83.8%	83.8%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	71/80	88.8%	88.8%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	72/80	90.0%	90.0%	–
`pharmacist-stage2-0405-pharmacotherapy`	75/80	93.8%	93.8%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	35/50	70.0%	70.0%	–
`tw-moex-115100-public-health-specialist-0801`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0802`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0803`	46.25/100	46.2%	92.5%	0.0%
`tw-moex-115100-public-health-specialist-0804`	42.5/100	42.5%	85.0%	0.0%
`tw-moex-115100-public-health-specialist-0805`	45/100	45.0%	90.0%	0.0%
`tw-moex-115100-public-health-specialist-0806`	48.75/100	48.8%	97.5%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-luna-low -o results

codex-gpt-5.6-luna-medium


Model	`codex:gpt-5.6-luna`
Effort	medium
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1002-general-1`	36/90	40.0%	90.0%	0.0%
`clinical-psychologist-115-2-1003-general-2`	36/90	40.0%	90.0%	0.0%
`clinical-psychologist-115-2-1004-special-1`	38/90	42.2%	95.0%	0.0%
`clinical-psychologist-115-2-1005-special-2`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1006-special-3`	39/90	43.3%	97.5%	0.0%
`counseling-and-psychotherapy-theories`	35/90	38.9%	87.5%	0.0%
`counseling-psychological-foundations`	39/90	43.3%	97.5%	0.0%
`counseling-psychotherapy-practice-and-ethics`	36/90	40.0%	90.0%	0.0%
`dietitian-0103-physiology-biochemistry`	49/50	98.0%	98.0%	–
`dietitian-0104-nutrition`	47/50	94.0%	94.0%	–
`dietitian-0105-public-health-nutrition`	41/50	82.0%	82.0%	–
`dietitian-0106-food-hygiene-safety`	46/50	92.0%	92.0%	–
`group-counseling-and-psychotherapy`	35/90	38.9%	87.5%	0.0%
`mental-health-and-abnormal-psychology`	37/90	41.1%	92.5%	0.0%
`ordinary-general-0114-law-english`	96/100	96.0%	96.0%	–
`ordinary-general-0406-administrative-law`	92/100	92.0%	92.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	75/80	93.8%	93.8%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	75/80	93.8%	93.8%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	70/80	87.5%	87.5%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	77/80	96.2%	96.2%	–
`pharmacist-stage2-0405-pharmacotherapy`	77/80	96.2%	96.2%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	50/50	100.0%	100.0%	–
`tw-moex-115100-public-health-specialist-0801`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0802`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0803`	46.25/100	46.2%	92.5%	0.0%
`tw-moex-115100-public-health-specialist-0804`	42.5/100	42.5%	85.0%	0.0%
`tw-moex-115100-public-health-specialist-0805`	42.5/100	42.5%	85.0%	0.0%
`tw-moex-115100-public-health-specialist-0806`	48.75/100	48.8%	97.5%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-luna-medium -o results

codex-gpt-5.6-luna-high


Model	`codex:gpt-5.6-luna`
Effort	high
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	39/90	43.3%	97.5%	0.0%
`clinical-psychologist-115-2-1002-general-1`	38/90	42.2%	95.0%	0.0%
`clinical-psychologist-115-2-1003-general-2`	38/90	42.2%	95.0%	0.0%
`clinical-psychologist-115-2-1004-special-1`	39/90	43.3%	97.5%	0.0%
`clinical-psychologist-115-2-1005-special-2`	38/90	42.2%	95.0%	0.0%
`clinical-psychologist-115-2-1006-special-3`	39/90	43.3%	97.5%	0.0%
`counseling-and-psychotherapy-theories`	40/90	44.4%	100.0%	0.0%
`counseling-psychological-foundations`	40/90	44.4%	100.0%	0.0%
`counseling-psychotherapy-practice-and-ethics`	38/90	42.2%	95.0%	0.0%
`dietitian-0103-physiology-biochemistry`	50/50	100.0%	100.0%	–
`dietitian-0104-nutrition`	48/50	96.0%	96.0%	–
`dietitian-0105-public-health-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0106-food-hygiene-safety`	50/50	100.0%	100.0%	–
`group-counseling-and-psychotherapy`	13/90	14.4%	32.5%	0.0%
`mental-health-and-abnormal-psychology`	37/90	41.1%	92.5%	0.0%
`ordinary-general-0114-law-english`	100/100	100.0%	100.0%	–
`ordinary-general-0406-administrative-law`	100/100	100.0%	100.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	77/80	96.2%	96.2%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	78/80	97.5%	97.5%	–
`pharmacist-stage2-0405-pharmacotherapy`	78/80	97.5%	97.5%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	50/50	100.0%	100.0%	–
`tw-moex-115100-public-health-specialist-0801`	48.75/100	48.8%	97.5%	0.0%
`tw-moex-115100-public-health-specialist-0802`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0803`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0804`	45/100	45.0%	90.0%	0.0%
`tw-moex-115100-public-health-specialist-0805`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0806`	48.75/100	48.8%	97.5%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-luna-high -o results

codex-gpt-5.6-luna-xhigh


Model	`codex:gpt-5.6-luna`
Effort	xhigh
Papers	29 from `skyhong2002/taiwan-professional-exams-115-2`
Judges	`openai:gpt-5.6-sol`
Runs per paper	2
Ingested by	any-to-bench 0.1.1
Ran	2026-08-23
Note	Fast mode; 29 papers; one sample per paper except administrative law uses repeat=2.

Paper	Score	%	Rule-graded	Judged
`case-assessment-and-psychological-evaluation`	40/90	44.4%	100.0%	0.0%
`clinical-psychologist-115-2-1002-general-1`	36/90	40.0%	90.0%	0.0%
`clinical-psychologist-115-2-1003-general-2`	37/90	41.1%	92.5%	0.0%
`clinical-psychologist-115-2-1004-special-1`	39/90	43.3%	97.5%	0.0%
`clinical-psychologist-115-2-1005-special-2`	39/90	43.3%	97.5%	0.0%
`clinical-psychologist-115-2-1006-special-3`	39/90	43.3%	97.5%	0.0%
`counseling-and-psychotherapy-theories`	40/90	44.4%	100.0%	0.0%
`counseling-psychological-foundations`	37/90	41.1%	92.5%	0.0%
`counseling-psychotherapy-practice-and-ethics`	40/90	44.4%	100.0%	0.0%
`dietitian-0103-physiology-biochemistry`	50/50	100.0%	100.0%	–
`dietitian-0104-nutrition`	50/50	100.0%	100.0%	–
`dietitian-0105-public-health-nutrition`	46/50	92.0%	92.0%	–
`dietitian-0106-food-hygiene-safety`	50/50	100.0%	100.0%	–
`group-counseling-and-psychotherapy`	39/90	43.3%	97.5%	0.0%
`mental-health-and-abnormal-psychology`	38/90	42.2%	95.0%	0.0%
`ordinary-general-0114-law-english`	100/100	100.0%	100.0%	–
`ordinary-general-0406-administrative-law`	100/100	100.0%	100.0%	–
`pharmacist-stage1-0401-pharmacology-medicinal-chemistry`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0402-analysis-pharmacognosy`	80/80	100.0%	100.0%	–
`pharmacist-stage1-0403-pharmaceutics-biopharmaceutics`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0404-dispensing-clinical-pharmacy`	76/80	95.0%	95.0%	–
`pharmacist-stage2-0405-pharmacotherapy`	80/80	100.0%	100.0%	–
`pharmacist-stage2-0406-pharmacy-administration-law`	50/50	100.0%	100.0%	–
`tw-moex-115100-public-health-specialist-0801`	28.75/100	28.8%	57.5%	0.0%
`tw-moex-115100-public-health-specialist-0802`	47.5/100	47.5%	95.0%	0.0%
`tw-moex-115100-public-health-specialist-0803`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0804`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0805`	50/100	50.0%	100.0%	0.0%
`tw-moex-115100-public-health-specialist-0806`	48.75/100	48.8%	97.5%	0.0%

a2b results fetch skyhong2002/taiwan-professional-exams-115-2-results --entry codex-gpt-5.6-luna-xhigh -o results