Jamba Large 1.7 Behavioral Fingerprint

How AI21's Jamba Large 1.7 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

AI21

Data generated

2026-07-08

Probe cells

15

Valid samples

450

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

24 / 30 answers

Favorite color

blue

14 / 30 answers

Coin flip: heads

82%

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 = 0.57 bit · uniform baseline 1.00 bit

AnswerCountShare
heads2686.7%
tails413.3%

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 = 2.79 bit · uniform baseline 5.64 bit

AnswerCountShare
zebra1033.3%
elephant516.7%
giraffe413.3%
dog310.0%
tiger26.7%
dolphin26.7%
cat26.7%
horse13.3%

+ 1 more answers

Random animal · Chinese

n = 30 · H = 2.68 bit · uniform baseline 5.64 bit

AnswerCountShare
狮子1033.3%
cat826.7%
310.0%
dog310.0%
13.3%
elephant13.3%
13.3%
panda13.3%

+ 2 more answers

Random city · English

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

AnswerCountShare
paris1136.7%
tokyo620.0%
mumbai413.3%
berlin310.0%
london26.7%
istanbul26.7%
cairo13.3%
moscow13.3%

Random city · Chinese

n = 30 · H = 2.32 bit · uniform baseline 5.64 bit

AnswerCountShare
上海1446.7%
伦敦620.0%
巴黎310.0%
柏林26.7%
北京26.7%
威斯康星13.3%
paris13.3%
london13.3%

Random color · English

n = 30 · H = 2.14 bit · uniform baseline 4.91 bit

AnswerCountShare
blue1446.7%
green620.0%
red310.0%
orange310.0%
purple310.0%
yellow13.3%

Random color · Chinese

n = 30 · H = 2.34 bit · uniform baseline 4.91 bit

AnswerCountShare
930.0%
red826.7%
516.7%
绿413.3%
blue310.0%
green13.3%

Random letter · English

n = 30 · H = 2.19 bit · uniform baseline 4.70 bit

AnswerCountShare
z1550.0%
g413.3%
f413.3%
c310.0%
w26.7%
u13.3%
k13.3%

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

AnswerCountShare
730100.0%

Random number 1-100 · English

n = 30 · H = 1.01 bit · uniform baseline 6.64 bit

AnswerCountShare
472480.0%
42310.0%
3726.7%
6313.3%

Random number 1-100 · Chinese

n = 30 · H = 1.25 bit · uniform baseline 6.64 bit

AnswerCountShare
472273.3%
42516.7%
713.3%
2313.3%
3713.3%

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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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Jamba Large 1.7 Behavioral Fingerprint — Favorite Random Numbers & Distribution | Tosea.ai