Kimi K2.5 Behavioral Fingerprint
How MoonshotAI's Kimi K2.5 answers one-word probe questions at temperature 1.0 — random numbers, colors, animals, coin flips — measured over 385 valid samples in the open dataset of "One Token Is Enough" (arXiv:2607.10252).
Vendor
MoonshotAI
Data generated
2026-07-08
Probe cells
15
Valid samples
385
Randomness score
35 / 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
11 / 26 answers
Favorite color
teal
8 / 26 answers
Coin flip: heads
94%
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 = 24 · H = 0.41 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 22 | 91.7% |
| tails | 2 | 8.3% |
Coin flip · Chinese
n = 24 · H = 0.25 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 23 | 95.8% |
| tails | 1 | 4.2% |
Favorite number · English
n = 29 · H = 1.07 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 22 | 75.9% |
| 42 | 5 | 17.2% |
| 4 | 1 | 3.4% |
| 17 | 1 | 3.4% |
Favorite number · Chinese
n = 28 · H = 0.71 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 24 | 85.7% |
| 42 | 3 | 10.7% |
| 8 | 1 | 3.6% |
Random animal · English
n = 21 · H = 2.80 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| axolotl | 6 | 28.6% |
| octopus | 4 | 19.0% |
| platypus | 4 | 19.0% |
| aardvark | 2 | 9.5% |
| penguin | 1 | 4.8% |
| alpaca | 1 | 4.8% |
| narwhal | 1 | 4.8% |
| dolphin | 1 | 4.8% |
+ 1 more answers
Random animal · Chinese
n = 28 · H = 3.09 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 企鹅 | 10 | 35.7% |
| 老虎 | 3 | 10.7% |
| 猫 | 2 | 7.1% |
| 长颈鹿 | 2 | 7.1% |
| 虎 | 2 | 7.1% |
| 猫头鹰 | 2 | 7.1% |
| 狐狸 | 2 | 7.1% |
| 羚羊 | 1 | 3.6% |
+ 4 more answers
Random city · English
n = 23 · H = 3.97 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| tbilisi | 3 | 13.0% |
| bishkek | 2 | 8.7% |
| vilnius | 2 | 8.7% |
| kyoto | 2 | 8.7% |
| riga | 2 | 8.7% |
| lviv | 1 | 4.3% |
| dushanbe | 1 | 4.3% |
| valencia | 1 | 4.3% |
+ 9 more answers
Random city · Chinese
n = 27 · H = 3.42 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 成都 | 7 | 25.9% |
| 东京 | 5 | 18.5% |
| 杭州 | 3 | 11.1% |
| 马德里 | 1 | 3.7% |
| 里斯本 | 1 | 3.7% |
| 特拉维夫 | 1 | 3.7% |
| 格拉斯哥 | 1 | 3.7% |
| 长沙 | 1 | 3.7% |
+ 7 more answers
Random color · English
n = 26 · H = 2.87 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| teal | 8 | 30.8% |
| magenta | 7 | 26.9% |
| azure | 2 | 7.7% |
| mauve | 2 | 7.7% |
| cyan | 1 | 3.8% |
| maroon | 1 | 3.8% |
| blue | 1 | 3.8% |
| red | 1 | 3.8% |
+ 3 more answers
Random color · Chinese
n = 27 · H = 1.99 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| 靛蓝 | 15 | 55.6% |
| 紫 | 4 | 14.8% |
| 青 | 4 | 14.8% |
| 青绿 | 1 | 3.7% |
| 紫罗兰 | 1 | 3.7% |
| 靛青 | 1 | 3.7% |
| 青柠 | 1 | 3.7% |
Random letter · English
n = 22 · H = 1.86 bit · uniform baseline 4.70 bit
| Answer | Count | Share |
|---|---|---|
| k | 10 | 45.5% |
| q | 8 | 36.4% |
| x | 1 | 4.5% |
| h | 1 | 4.5% |
| j | 1 | 4.5% |
| z | 1 | 4.5% |
Random number 1-10 · English
n = 27 · H = 0.00 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 27 | 100.0% |
Random number 1-10 · Chinese
n = 26 · H = 0.47 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 24 | 92.3% |
| 5 | 1 | 3.8% |
| 6 | 1 | 3.8% |
Random number 1-100 · English
n = 26 · H = 1.81 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 47 | 11 | 42.3% |
| 73 | 10 | 38.5% |
| 37 | 2 | 7.7% |
| 42 | 2 | 7.7% |
| 34 | 1 | 3.8% |
Random number 1-100 · Chinese
n = 27 · H = 2.16 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 47 | 11 | 40.7% |
| 73 | 6 | 22.2% |
| 42 | 5 | 18.5% |
| 37 | 3 | 11.1% |
| 43 | 1 | 3.7% |
| 57 | 1 | 3.7% |
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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.