Voxtral Small 24B 2507 Behavioral Fingerprint
How Mistral's Voxtral Small 24B 2507 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
Mistral
Data generated
2026-07-08
Probe cells
15
Valid samples
450
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
17 / 30 answers
Favorite color
blue
24 / 30 answers
Coin flip: heads
38%
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 = 0.57 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| tails | 26 | 86.7% |
| heads | 4 | 13.3% |
Coin flip · Chinese
n = 30 · H = 0.95 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 19 | 63.3% |
| tails | 11 | 36.7% |
Favorite number · English
n = 30 · H = 1.11 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 19 | 63.3% |
| 7 | 10 | 33.3% |
| 1 | 1 | 3.3% |
Favorite number · Chinese
n = 30 · H = 0.91 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 24 | 80.0% |
| 42 | 4 | 13.3% |
| 3 | 2 | 6.7% |
Random animal · English
n = 30 · H = 1.64 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| elephant | 16 | 53.3% |
| lion | 8 | 26.7% |
| dog | 4 | 13.3% |
| giraffe | 2 | 6.7% |
Random animal · Chinese
n = 30 · H = 2.37 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 狮子 | 11 | 36.7% |
| 狗 | 8 | 26.7% |
| 猫 | 4 | 13.3% |
| 老虎 | 2 | 6.7% |
| 大象 | 2 | 6.7% |
| 熊 | 2 | 6.7% |
| 鸟 | 1 | 3.3% |
Random city · English
n = 30 · H = 1.23 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| paris | 18 | 60.0% |
| tokyo | 10 | 33.3% |
| london | 2 | 6.7% |
Random city · Chinese
n = 30 · H = 1.73 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 巴黎 | 16 | 53.3% |
| 北京 | 7 | 23.3% |
| 上海 | 5 | 16.7% |
| 东京 | 1 | 3.3% |
| 纽约 | 1 | 3.3% |
Random color · English
n = 30 · H = 0.72 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| blue | 24 | 80.0% |
| red | 6 | 20.0% |
Random color · Chinese
n = 30 · H = 0.70 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| 蓝 | 26 | 86.7% |
| 红 | 2 | 6.7% |
| 绿 | 2 | 6.7% |
Random letter · English
n = 30 · H = 2.51 bit · uniform baseline 4.70 bit
| Answer | Count | Share |
|---|---|---|
| a | 12 | 40.0% |
| b | 6 | 20.0% |
| g | 3 | 10.0% |
| j | 3 | 10.0% |
| e | 2 | 6.7% |
| c | 2 | 6.7% |
| f | 1 | 3.3% |
| k | 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 = 1.69 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 18 | 60.0% |
| 5 | 6 | 20.0% |
| 3 | 2 | 6.7% |
| 4 | 2 | 6.7% |
| 8 | 2 | 6.7% |
Random number 1-100 · English
n = 30 · H = 1.16 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 17 | 56.7% |
| 72 | 12 | 40.0% |
| 73 | 1 | 3.3% |
Random number 1-100 · Chinese
n = 30 · H = 2.47 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 10 | 33.3% |
| 73 | 7 | 23.3% |
| 72 | 6 | 20.0% |
| 67 | 3 | 10.0% |
| 37 | 1 | 3.3% |
| 56 | 1 | 3.3% |
| 57 | 1 | 3.3% |
| 63 | 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.