GPT-4o-mini Behavioral Fingerprint
How OpenAI's GPT-4o-mini 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
23 / 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
18 / 30 answers
Favorite color
turquoise
18 / 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 = 0.88 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 21 | 70.0% |
| tails | 9 | 30.0% |
Coin flip · Chinese
n = 30 · H = 0.00 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 30 | 100.0% |
Favorite number · English
n = 30 · H = 0.21 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 29 | 96.7% |
| 42 | 1 | 3.3% |
Favorite number · Chinese
n = 30 · H = 0.21 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 29 | 96.7% |
| 8 | 1 | 3.3% |
Random animal · English
n = 30 · H = 2.06 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| giraffe | 14 | 46.7% |
| elephant | 8 | 26.7% |
| kangaroo | 4 | 13.3% |
| octopus | 1 | 3.3% |
| penguin | 1 | 3.3% |
| panda | 1 | 3.3% |
| zebra | 1 | 3.3% |
Random animal · Chinese
n = 30 · H = 2.80 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 海豚 | 11 | 36.7% |
| 猫 | 6 | 20.0% |
| 大象 | 3 | 10.0% |
| 猩猩 | 3 | 10.0% |
| 企鹅 | 1 | 3.3% |
| 蛇 | 1 | 3.3% |
| 虎 | 1 | 3.3% |
| 松鼠 | 1 | 3.3% |
+ 3 more answers
Random city · English
n = 30 · H = 1.75 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| tokyo | 18 | 60.0% |
| berlin | 5 | 16.7% |
| oslo | 4 | 13.3% |
| paris | 1 | 3.3% |
| madrid | 1 | 3.3% |
| zurich | 1 | 3.3% |
Random city · Chinese
n = 30 · H = 0.67 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 东京 | 26 | 86.7% |
| 巴黎 | 3 | 10.0% |
| 巴塞罗那 | 1 | 3.3% |
Random color · English
n = 30 · H = 1.75 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| turquoise | 18 | 60.0% |
| cerulean | 7 | 23.3% |
| cyan | 1 | 3.3% |
| azure | 1 | 3.3% |
| blue | 1 | 3.3% |
| magenta | 1 | 3.3% |
| chartreuse | 1 | 3.3% |
Random color · Chinese
n = 30 · H = 0.00 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| 蓝 | 30 | 100.0% |
Random letter · English
n = 30 · H = 2.22 bit · uniform baseline 4.70 bit
| Answer | Count | Share |
|---|---|---|
| g | 10 | 33.3% |
| q | 7 | 23.3% |
| k | 7 | 23.3% |
| m | 4 | 13.3% |
| r | 1 | 3.3% |
| j | 1 | 3.3% |
Random number 1-10 · English
n = 30 · H = 0.00 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 30 | 100.0% |
Random number 1-10 · Chinese
n = 30 · H = 0.00 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 30 | 100.0% |
Random number 1-100 · English
n = 30 · H = 1.59 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 57 | 18 | 60.0% |
| 42 | 5 | 16.7% |
| 47 | 4 | 13.3% |
| 37 | 3 | 10.0% |
Random number 1-100 · Chinese
n = 30 · H = 1.01 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 57 | 24 | 80.0% |
| 42 | 3 | 10.0% |
| 37 | 2 | 6.7% |
| 47 | 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.