Claude Sonnet 4.5 Behavioral Fingerprint

How Anthropic's Claude Sonnet 4.5 answers one-word probe questions at temperature 1.0 — random numbers, colors, animals, coin flips — measured over 450 valid samples in the open dataset of "One Token Is Enough" (arXiv:2607.10252).

Vendor

Anthropic

Data generated

2026-07-08

Probe cells

15

Valid samples

450

Randomness score

8 / 100

Mean normalized entropy across cells, 0–100. 100 would be a uniform-random baseline; real models score far lower.

Signature answers

Favorite random number (1–100)

47

28 / 30 answers

Favorite color

blue

30 / 30 answers

Coin flip: heads

100%

Share of heads across coin-flip cells.

Answer distributions by probe cell

Empirical distributions of normalized one-word answers, per task and language. H is the Shannon entropy in bits; the uniform baseline is log2 of the answer-domain size.

Coin flip · English

n = 30 · H = 0.00 bit · uniform baseline 1.00 bit

AnswerCountShare
heads30100.0%

Coin flip · Chinese

n = 30 · H = 0.00 bit · uniform baseline 1.00 bit

AnswerCountShare
heads30100.0%

Favorite number · English

n = 30 · H = 0.00 bit · uniform baseline 13.29 bit

AnswerCountShare
730100.0%

Favorite number · Chinese

n = 30 · H = 0.00 bit · uniform baseline 13.29 bit

AnswerCountShare
730100.0%

Random animal · English

n = 30 · H = 0.00 bit · uniform baseline 5.64 bit

AnswerCountShare
elephant30100.0%

Random animal · Chinese

n = 30 · H = 1.64 bit · uniform baseline 5.64 bit

AnswerCountShare
企鹅1756.7%
长颈鹿930.0%
大象13.3%
熊猫13.3%
海豚13.3%
袋鼠13.3%

Random city · English

n = 30 · H = 0.98 bit · uniform baseline 5.64 bit

AnswerCountShare
toronto2273.3%
tokyo723.3%
berlin13.3%

Random city · Chinese

n = 30 · H = 2.63 bit · uniform baseline 5.64 bit

AnswerCountShare
京都1136.7%
巴塞罗那516.7%
布拉格413.3%
巴黎310.0%
柏林26.7%
悉尼26.7%
墨尔本26.7%
东京13.3%

Random color · English

n = 30 · H = 0.00 bit · uniform baseline 4.91 bit

AnswerCountShare
blue30100.0%

Random color · Chinese

n = 30 · H = 0.00 bit · uniform baseline 4.91 bit

AnswerCountShare
30100.0%

Random letter · English

n = 30 · H = 0.00 bit · uniform baseline 4.70 bit

AnswerCountShare
m30100.0%

Random number 1-10 · English

n = 30 · H = 0.00 bit · uniform baseline 3.32 bit

AnswerCountShare
730100.0%

Random number 1-10 · Chinese

n = 30 · H = 0.00 bit · uniform baseline 3.32 bit

AnswerCountShare
730100.0%

Random number 1-100 · English

n = 30 · H = 0.35 bit · uniform baseline 6.64 bit

AnswerCountShare
472893.3%
4226.7%

Random number 1-100 · Chinese

n = 30 · H = 0.95 bit · uniform baseline 6.64 bit

AnswerCountShare
421963.3%
471136.7%

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Data source & license

Distributions: Tomáš Bruckner, "One Token Is Enough" (arXiv:2607.10252), official dataset Zenodo DOI 10.5281/zenodo.21278557, licensed CC-BY-4.0. Collected via OpenRouter at temperature 1.0 under the paper's fixed minimal one-word system prompt; answer keys are re-normalized with the checker's pipeline (color aliases, number words, coin h/t) so live probes are directly comparable.

Paper on arXivDataset on ZenodoCC-BY-4.0 license

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Claude Sonnet 4.5 Behavioral Fingerprint — Favorite Random Numbers & Distribution | Tosea.ai