GPT-4.1 Nano Behavioral Fingerprint

How OpenAI's GPT-4.1 Nano answers one-word probe questions at temperature 1.0 — random numbers, colors, animals, coin flips — measured over 444 valid samples in the open dataset of "One Token Is Enough" (arXiv:2607.10252).

Vendor

OpenAI

Data generated

2026-07-08

Probe cells

15

Valid samples

444

Randomness score

33 / 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

10 / 30 answers

Favorite color

blue

9 / 30 answers

Coin flip: heads

65%

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 = 1.00 bit · uniform baseline 1.00 bit

AnswerCountShare
heads1653.3%
tails1446.7%

Coin flip · Chinese

n = 30 · H = 0.78 bit · uniform baseline 1.00 bit

AnswerCountShare
heads2376.7%
tails723.3%

Favorite number · English

n = 25 · H = 0.40 bit · uniform baseline 13.29 bit

AnswerCountShare
72392.0%
4228.0%

Favorite number · Chinese

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

AnswerCountShare
730100.0%

Random animal · English

n = 30 · H = 2.47 bit · uniform baseline 5.64 bit

AnswerCountShare
elephant1136.7%
giraffe620.0%
koala620.0%
otter26.7%
tiger26.7%
leonardo13.3%
jaguar13.3%
kangaroo13.3%

Random animal · Chinese

n = 30 · H = 2.65 bit · uniform baseline 5.64 bit

AnswerCountShare
1033.3%
930.0%
26.7%
26.7%
26.7%
狮子13.3%
13.3%
斑马13.3%

+ 2 more answers

Random city · English

n = 30 · H = 3.24 bit · uniform baseline 5.64 bit

AnswerCountShare
lagos1033.3%
kyoto413.3%
tokyo310.0%
oslo26.7%
dublin26.7%
lisbon13.3%
cairo13.3%
helsinki13.3%

+ 6 more answers

Random city · Chinese

n = 30 · H = 0.67 bit · uniform baseline 5.64 bit

AnswerCountShare
东京2686.7%
巴黎310.0%
京都13.3%

Random color · English

n = 30 · H = 2.75 bit · uniform baseline 4.91 bit

AnswerCountShare
blue930.0%
violet620.0%
azure413.3%
turquoise310.0%
vermilion26.7%
crimson26.7%
magenta26.7%
cyan26.7%

Random color · Chinese

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

AnswerCountShare
30100.0%

Random letter · English

n = 30 · H = 1.82 bit · uniform baseline 4.70 bit

AnswerCountShare
m1653.3%
k826.7%
q310.0%
g13.3%
h13.3%
n13.3%

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 = 29 · H = 0.00 bit · uniform baseline 3.32 bit

AnswerCountShare
729100.0%

Random number 1-100 · English

n = 30 · H = 1.83 bit · uniform baseline 6.64 bit

AnswerCountShare
471033.3%
571033.3%
73826.7%
4226.7%

Random number 1-100 · Chinese

n = 30 · H = 2.54 bit · uniform baseline 6.64 bit

AnswerCountShare
421240.0%
73516.7%
37310.0%
47310.0%
57310.0%
5626.7%
4513.3%
5813.3%

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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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