GPT-4 Behavioral Fingerprint
How OpenAI's GPT-4 answers one-word probe questions at temperature 1.0 — random numbers, colors, animals, coin flips — measured over 445 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
445
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)
42
21 / 30 answers
Favorite color
blue
20 / 30 answers
Coin flip: heads
87%
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
| Answer | Count | Share |
|---|---|---|
| heads | 23 | 76.7% |
| tails | 7 | 23.3% |
Coin flip · Chinese
n = 30 · H = 0.21 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 29 | 96.7% |
| tails | 1 | 3.3% |
Favorite number · English
n = 25 · H = 1.32 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 15 | 60.0% |
| 42 | 7 | 28.0% |
| 0 | 3 | 12.0% |
Favorite number · Chinese
n = 30 · H = 0.56 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 27 | 90.0% |
| 42 | 2 | 6.7% |
| 3 | 1 | 3.3% |
Random animal · English
n = 30 · H = 2.40 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| elephant | 10 | 33.3% |
| cheetah | 8 | 26.7% |
| tiger | 4 | 13.3% |
| giraffe | 4 | 13.3% |
| dolphin | 2 | 6.7% |
| leopard | 1 | 3.3% |
| panther | 1 | 3.3% |
Random animal · Chinese
n = 30 · H = 3.47 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 狐狸 | 6 | 20.0% |
| 熊猫 | 5 | 16.7% |
| 狮子 | 4 | 13.3% |
| 企鹅 | 2 | 6.7% |
| 狐 | 2 | 6.7% |
| 豹子 | 2 | 6.7% |
| 猫 | 2 | 6.7% |
| 鹦鹉 | 1 | 3.3% |
+ 6 more answers
Random city · English
n = 30 · H = 1.92 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| tokyo | 17 | 56.7% |
| paris | 6 | 20.0% |
| berlin | 3 | 10.0% |
| amsterdam | 1 | 3.3% |
| london | 1 | 3.3% |
| madrid | 1 | 3.3% |
| dallas | 1 | 3.3% |
Random city · Chinese
n = 30 · H = 2.07 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 巴黎 | 15 | 50.0% |
| 东京 | 7 | 23.3% |
| 北京 | 3 | 10.0% |
| 上海 | 2 | 6.7% |
| 杭州 | 1 | 3.3% |
| 哈尔滨 | 1 | 3.3% |
| 伦敦 | 1 | 3.3% |
Random color · English
n = 30 · H = 1.89 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| blue | 20 | 66.7% |
| cerulean | 2 | 6.7% |
| purple | 2 | 6.7% |
| orange | 1 | 3.3% |
| turquoise | 1 | 3.3% |
| yellow | 1 | 3.3% |
| teal | 1 | 3.3% |
| pink | 1 | 3.3% |
+ 1 more answers
Random color · Chinese
n = 30 · H = 1.80 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| 蓝 | 17 | 56.7% |
| 红 | 7 | 23.3% |
| 紫 | 2 | 6.7% |
| 绿 | 2 | 6.7% |
| 靛蓝 | 1 | 3.3% |
| 黄 | 1 | 3.3% |
Random letter · English
n = 30 · H = 2.21 bit · uniform baseline 4.70 bit
| Answer | Count | Share |
|---|---|---|
| g | 13 | 43.3% |
| k | 5 | 16.7% |
| m | 5 | 16.7% |
| j | 3 | 10.0% |
| q | 3 | 10.0% |
| x | 1 | 3.3% |
Random number 1-10 · English
n = 30 · H = 0.42 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 28 | 93.3% |
| 3 | 1 | 3.3% |
| 6 | 1 | 3.3% |
Random number 1-10 · Chinese
n = 30 · H = 0.35 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 28 | 93.3% |
| 5 | 2 | 6.7% |
Random number 1-100 · English
n = 30 · H = 1.61 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 21 | 70.0% |
| 37 | 3 | 10.0% |
| 57 | 2 | 6.7% |
| 34 | 1 | 3.3% |
| 43 | 1 | 3.3% |
| 63 | 1 | 3.3% |
| 72 | 1 | 3.3% |
Random number 1-100 · Chinese
n = 30 · H = 1.21 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 23 | 76.7% |
| 57 | 3 | 10.0% |
| 47 | 2 | 6.7% |
| 37 | 1 | 3.3% |
| 67 | 1 | 3.3% |
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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.