DeepSeek V4 Pro Behavioral Fingerprint

How DeepSeek's DeepSeek V4 Pro 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

DeepSeek

Data generated

2026-07-08

Probe cells

15

Valid samples

449

Randomness score

34 / 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

7 / 30 answers

Favorite color

cerulean

17 / 30 answers

Coin flip: heads

98%

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 = 0.21 bit · uniform baseline 1.00 bit

AnswerCountShare
heads2996.7%
tails13.3%

Favorite number · English

n = 30 · H = 0.65 bit · uniform baseline 13.29 bit

AnswerCountShare
72583.3%
42516.7%

Favorite number · Chinese

n = 30 · H = 0.42 bit · uniform baseline 13.29 bit

AnswerCountShare
72893.3%
413.3%
4213.3%

Random animal · English

n = 30 · H = 2.94 bit · uniform baseline 5.64 bit

AnswerCountShare
elephant1343.3%
platypus310.0%
okapi26.7%
giraffe26.7%
dog26.7%
anteater13.3%
salamander13.3%
capybara13.3%

+ 5 more answers

Random animal · Chinese

n = 30 · H = 2.94 bit · uniform baseline 5.64 bit

AnswerCountShare
企鹅826.7%
620.0%
大象620.0%
海豚26.7%
26.7%
鲸鱼13.3%
麻雀13.3%
袋鼠13.3%

+ 3 more answers

Random city · English

n = 30 · H = 3.42 bit · uniform baseline 5.64 bit

AnswerCountShare
london826.7%
tokyo413.3%
paris413.3%
seoul310.0%
kabul13.3%
tulsa13.3%
zurich13.3%
madrid13.3%

+ 7 more answers

Random city · Chinese

n = 30 · H = 1.85 bit · uniform baseline 5.64 bit

AnswerCountShare
巴黎1550.0%
东京1033.3%
奥斯陆13.3%
卢森堡市13.3%
维也纳13.3%
伦敦13.3%
纽约13.3%

Random color · English

n = 30 · H = 2.05 bit · uniform baseline 4.91 bit

AnswerCountShare
cerulean1756.7%
turquoise310.0%
azure310.0%
indigo310.0%
lavender26.7%
magenta13.3%
teal13.3%

Random color · Chinese

n = 30 · H = 2.44 bit · uniform baseline 4.91 bit

AnswerCountShare
蔚蓝1343.3%
靛蓝826.7%
蓝宝石26.7%
碧蓝13.3%
13.3%
靛青13.3%
钴蓝13.3%
13.3%

+ 2 more answers

Random letter · English

n = 30 · H = 3.10 bit · uniform baseline 4.70 bit

AnswerCountShare
m723.3%
k723.3%
j413.3%
q310.0%
v26.7%
u13.3%
s13.3%
g13.3%

+ 4 more answers

Random number 1-10 · English

n = 29 · H = 0.79 bit · uniform baseline 3.32 bit

AnswerCountShare
72586.2%
626.9%
513.4%
813.4%

Random number 1-10 · Chinese

n = 30 · H = 0.88 bit · uniform baseline 3.32 bit

AnswerCountShare
72583.3%
4310.0%
313.3%
513.3%

Random number 1-100 · English

n = 30 · H = 3.24 bit · uniform baseline 6.64 bit

AnswerCountShare
42723.3%
47620.0%
57413.3%
67310.0%
7526.7%
1213.3%
2513.3%
2713.3%

+ 5 more answers

Random number 1-100 · Chinese

n = 30 · H = 1.61 bit · uniform baseline 6.64 bit

AnswerCountShare
372170.0%
42310.0%
5726.7%
3813.3%
4313.3%
5313.3%
7113.3%

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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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