GLM 4.6 Behavioral Fingerprint

How Z.ai's GLM 4.6 answers one-word probe questions at temperature 1.0 — random numbers, colors, animals, coin flips — measured over 449 valid samples in the open dataset of "One Token Is Enough" (arXiv:2607.10252).

Vendor

Z.ai

Data generated

2026-07-08

Probe cells

15

Valid samples

449

Randomness score

35 / 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)

42

24 / 30 answers

Favorite color

turquoise

15 / 30 answers

Coin flip: heads

85%

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 = 0.78 bit · uniform baseline 1.00 bit

AnswerCountShare
heads2376.7%
tails723.3%

Coin flip · Chinese

n = 30 · H = 0.35 bit · uniform baseline 1.00 bit

AnswerCountShare
heads2893.3%
tails26.7%

Favorite number · English

n = 30 · H = 0.67 bit · uniform baseline 13.29 bit

AnswerCountShare
422686.7%
7310.0%
4413.3%

Favorite number · Chinese

n = 29 · H = 1.20 bit · uniform baseline 13.29 bit

AnswerCountShare
422069.0%
7724.1%
113.4%
313.4%

Random animal · English

n = 30 · H = 1.35 bit · uniform baseline 5.64 bit

AnswerCountShare
elephant1446.7%
giraffe1446.7%
okapi13.3%
platypus13.3%

Random animal · Chinese

n = 30 · H = 1.91 bit · uniform baseline 5.64 bit

AnswerCountShare
长颈鹿1860.0%
413.3%
熊猫310.0%
大象26.7%
考拉13.3%
狮子13.3%
長頸鹿13.3%

Random city · English

n = 30 · H = 4.10 bit · uniform baseline 5.64 bit

AnswerCountShare
tokyo620.0%
oslo310.0%
paris26.7%
chicago26.7%
quito13.3%
barcelona13.3%
sydney13.3%
sanmarino13.3%

+ 13 more answers

Random city · Chinese

n = 30 · H = 3.54 bit · uniform baseline 5.64 bit

AnswerCountShare
上海516.7%
巴黎413.3%
东京413.3%
伦敦310.0%
柏林310.0%
伊斯坦布尔26.7%
京都26.7%
开罗13.3%

+ 6 more answers

Random color · English

n = 30 · H = 2.57 bit · uniform baseline 4.91 bit

AnswerCountShare
turquoise1550.0%
cerulean310.0%
teal310.0%
mauve26.7%
maroon13.3%
emerald13.3%
chartreuse13.3%
azure13.3%

+ 3 more answers

Random color · Chinese

n = 30 · H = 2.11 bit · uniform baseline 4.91 bit

AnswerCountShare
1860.0%
绿310.0%
26.7%
26.7%
靛蓝13.3%
粉红13.3%
天蓝13.3%
blue13.3%

+ 1 more answers

Random letter · English

n = 30 · H = 2.12 bit · uniform baseline 4.70 bit

AnswerCountShare
k1653.3%
q620.0%
p26.7%
g26.7%
m13.3%
r13.3%
s13.3%
t13.3%

Random number 1-10 · English

n = 30 · H = 0.21 bit · uniform baseline 3.32 bit

AnswerCountShare
72996.7%
313.3%

Random number 1-10 · Chinese

n = 30 · H = 0.42 bit · uniform baseline 3.32 bit

AnswerCountShare
72893.3%
313.3%
413.3%

Random number 1-100 · English

n = 30 · H = 0.91 bit · uniform baseline 6.64 bit

AnswerCountShare
422480.0%
73413.3%
3726.7%

Random number 1-100 · Chinese

n = 30 · H = 1.57 bit · uniform baseline 6.64 bit

AnswerCountShare
421756.7%
73826.7%
37310.0%
5726.7%

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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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