Llama 3.2 1B Instruct Behavioral Fingerprint
How Meta's Llama 3.2 1B Instruct 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
Meta
Data generated
2026-07-08
Probe cells
15
Valid samples
450
Randomness score
0 / 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)
23
30 / 30 answers
Favorite color
blue
30 / 30 answers
Coin flip: heads
50%
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 = 0.00 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| tails | 30 | 100.0% |
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 = 0.00 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 2 | 30 | 100.0% |
Favorite number · Chinese
n = 30 · H = 0.00 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 8 | 30 | 100.0% |
Random animal · English
n = 30 · H = 0.00 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| polar | 30 | 100.0% |
Random animal · Chinese
n = 30 · H = 0.00 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 象 | 30 | 100.0% |
Random city · English
n = 30 · H = 0.00 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| tokyo | 30 | 100.0% |
Random city · Chinese
n = 30 · H = 0.00 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 巴黎 | 30 | 100.0% |
Random color · English
n = 30 · H = 0.00 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| blue | 30 | 100.0% |
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 |
|---|---|---|
| z | 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 |
|---|---|---|
| 5 | 30 | 100.0% |
Random number 1-100 · English
n = 30 · H = 0.00 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 23 | 30 | 100.0% |
Random number 1-100 · Chinese
n = 30 · H = 0.00 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 67 | 30 | 100.0% |
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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.