Ling-2.6-1T Behavioral Fingerprint
How inclusionAI's Ling-2.6-1T 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
inclusionAI
Data generated
2026-07-08
Probe cells
15
Valid samples
450
Randomness score
14 / 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
29 / 30 answers
Favorite color
cyan
13 / 30 answers
Coin flip: heads
98%
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 = 0.21 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 29 | 96.7% |
| tails | 1 | 3.3% |
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% |
| 4 | 1 | 3.3% |
Favorite number · Chinese
n = 30 · H = 0.00 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 30 | 100.0% |
Random animal · English
n = 30 · H = 1.45 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| elephant | 21 | 70.0% |
| giraffe | 3 | 10.0% |
| octopus | 3 | 10.0% |
| kangaroo | 2 | 6.7% |
| tiger | 1 | 3.3% |
Random animal · Chinese
n = 30 · H = 0.77 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 猫 | 26 | 86.7% |
| 狮子 | 2 | 6.7% |
| 老虎 | 1 | 3.3% |
| 熊猫 | 1 | 3.3% |
Random city · English
n = 30 · H = 2.48 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| tokyo | 16 | 53.3% |
| kyoto | 3 | 10.0% |
| paris | 2 | 6.7% |
| nairobi | 2 | 6.7% |
| sydney | 1 | 3.3% |
| vancouver | 1 | 3.3% |
| berlin | 1 | 3.3% |
| toronto | 1 | 3.3% |
+ 3 more answers
Random city · Chinese
n = 30 · H = 2.36 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 东京 | 10 | 33.3% |
| 上海 | 7 | 23.3% |
| 巴黎 | 6 | 20.0% |
| 伦敦 | 4 | 13.3% |
| 纽约 | 1 | 3.3% |
| 北京 | 1 | 3.3% |
| 重庆 | 1 | 3.3% |
Random color · English
n = 30 · H = 2.19 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| cyan | 13 | 43.3% |
| cerulean | 6 | 20.0% |
| blue | 4 | 13.3% |
| crimson | 4 | 13.3% |
| azure | 2 | 6.7% |
| teal | 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 = 0.00 bit · uniform baseline 4.70 bit
| Answer | Count | Share |
|---|---|---|
| k | 30 | 100.0% |
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 = 0.21 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 29 | 96.7% |
| 47 | 1 | 3.3% |
Random number 1-100 · Chinese
n = 30 · H = 0.47 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 27 | 90.0% |
| 47 | 3 | 10.0% |
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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.