GPT-3.5 Turbo (older v0613) Behavioral Fingerprint

How OpenAI's GPT-3.5 Turbo (older v0613) 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

OpenAI

Data generated

2026-07-08

Probe cells

15

Valid samples

450

Randomness score

22 / 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)

57

21 / 30 answers

Favorite color

blue

29 / 30 answers

Coin flip: heads

83%

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 = 0.84 bit · uniform baseline 1.00 bit

AnswerCountShare
heads2273.3%
tails826.7%

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 = 0.47 bit · uniform baseline 13.29 bit

AnswerCountShare
72790.0%
42310.0%

Favorite number · Chinese

n = 30 · H = 0.21 bit · uniform baseline 13.29 bit

AnswerCountShare
72996.7%
813.3%

Random animal · English

n = 30 · H = 0.72 bit · uniform baseline 5.64 bit

AnswerCountShare
elephant2480.0%
dolphin620.0%

Random animal · Chinese

n = 30 · H = 2.97 bit · uniform baseline 5.64 bit

AnswerCountShare
1343.3%
狮子26.7%
海豚26.7%
大象26.7%
袋鼠26.7%
鲸鱼26.7%
13.3%
豹子13.3%

+ 5 more answers

Random city · English

n = 30 · H = 1.57 bit · uniform baseline 5.64 bit

AnswerCountShare
tokyo1963.3%
paris620.0%
oslo26.7%
kyoto26.7%
berlin13.3%

Random city · Chinese

n = 30 · H = 0.95 bit · uniform baseline 5.64 bit

AnswerCountShare
巴黎1963.3%
东京1136.7%

Random color · English

n = 30 · H = 0.21 bit · uniform baseline 4.91 bit

AnswerCountShare
blue2996.7%
turquoise13.3%

Random color · Chinese

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

AnswerCountShare
30100.0%

Random letter · English

n = 30 · H = 2.02 bit · uniform baseline 4.70 bit

AnswerCountShare
g1136.7%
m826.7%
k723.3%
q310.0%
r13.3%

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 = 1.32 bit · uniform baseline 6.64 bit

AnswerCountShare
572170.0%
47620.0%
2713.3%
3713.3%
7313.3%

Random number 1-100 · Chinese

n = 30 · H = 2.07 bit · uniform baseline 6.64 bit

AnswerCountShare
571756.7%
47516.7%
4226.7%
7326.7%
2713.3%
3713.3%
5813.3%
7213.3%

Want to verify your API really serves GPT-3.5 Turbo (older v0613)?

Point the free fingerprint checker at your endpoint: it samples the same probe questions from your browser and compares the distributions against this reference. Your API key never leaves your browser.

Verify your endpoint

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

More OpenAI model fingerprints

Browse all 167 model fingerprints

GPT-3.5 Turbo (older v0613) Behavioral Fingerprint — Favorite Random Numbers & Distribution | Tosea.ai