Gemma 2 27B Behavioral Fingerprint

How Google's Gemma 2 27B 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

Google

Data generated

2026-07-08

Probe cells

15

Valid samples

444

Randomness score

32 / 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)

37

9 / 30 answers

Favorite color

indigo

21 / 30 answers

Coin flip: heads

41%

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 = 0.35 bit · uniform baseline 1.00 bit

AnswerCountShare
tails2893.3%
heads26.7%

Coin flip · Chinese

n = 28 · H = 0.75 bit · uniform baseline 1.00 bit

AnswerCountShare
heads2278.6%
tails621.4%

Favorite number · English

n = 27 · H = 1.39 bit · uniform baseline 13.29 bit

AnswerCountShare
71244.4%
421244.4%
17311.1%

Favorite number · Chinese

n = 29 · H = 0.00 bit · uniform baseline 13.29 bit

AnswerCountShare
729100.0%

Random animal · English

n = 30 · H = 2.56 bit · uniform baseline 5.64 bit

AnswerCountShare
giraffe1033.3%
elephant930.0%
kangaroo310.0%
tiger26.7%
dolphin26.7%
platypus13.3%
cat13.3%
sloth13.3%

+ 1 more answers

Random animal · Chinese

n = 30 · H = 1.05 bit · uniform baseline 5.64 bit

AnswerCountShare
2376.7%
大象516.7%
熊猫13.3%
斑马13.3%

Random city · English

n = 30 · H = 3.28 bit · uniform baseline 5.64 bit

AnswerCountShare
paris930.0%
london516.7%
tokyo310.0%
nairobi26.7%
prague26.7%
lisbon13.3%
florence13.3%
kyoto13.3%

+ 6 more answers

Random city · Chinese

n = 30 · H = 1.69 bit · uniform baseline 5.64 bit

AnswerCountShare
巴黎1756.7%
东京620.0%
伦敦516.7%
悉尼13.3%
柏林13.3%

Random color · English

n = 30 · H = 1.63 bit · uniform baseline 4.91 bit

AnswerCountShare
indigo2170.0%
green26.7%
azure26.7%
teal26.7%
blue13.3%
cyan13.3%
violet13.3%

Random color · Chinese

n = 30 · H = 1.60 bit · uniform baseline 4.91 bit

AnswerCountShare
1446.7%
绿1136.7%
413.3%
13.3%

Random letter · English

n = 30 · H = 2.73 bit · uniform baseline 4.70 bit

AnswerCountShare
q930.0%
j826.7%
k310.0%
t26.7%
g26.7%
z26.7%
p26.7%
l13.3%

+ 1 more answers

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 = 0.21 bit · uniform baseline 3.32 bit

AnswerCountShare
72996.7%
513.3%

Random number 1-100 · English

n = 30 · H = 2.51 bit · uniform baseline 6.64 bit

AnswerCountShare
37930.0%
42930.0%
73413.3%
72310.0%
6726.7%
3213.3%
6213.3%
7413.3%

Random number 1-100 · Chinese

n = 30 · H = 2.34 bit · uniform baseline 6.64 bit

AnswerCountShare
421446.7%
73516.7%
37413.3%
5326.7%
7726.7%
5213.3%
7213.3%
8713.3%

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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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