Llama 4 Maverick Behavioral Fingerprint
How Meta's Llama 4 Maverick 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
21 / 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)
53
29 / 30 answers
Favorite color
blue
30 / 30 answers
Coin flip: heads
57%
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 = 0.65 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| heads | 25 | 83.3% |
| tails | 5 | 16.7% |
Coin flip · Chinese
n = 30 · H = 0.88 bit · uniform baseline 1.00 bit
| Answer | Count | Share |
|---|---|---|
| tails | 21 | 70.0% |
| heads | 9 | 30.0% |
Favorite number · English
n = 30 · H = 0.21 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 29 | 96.7% |
| 1 | 1 | 3.3% |
Favorite number · Chinese
n = 30 · H = 0.35 bit · uniform baseline 13.29 bit
| Answer | Count | Share |
|---|---|---|
| 42 | 28 | 93.3% |
| 7 | 2 | 6.7% |
Random animal · English
n = 30 · H = 1.30 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| tiger | 18 | 60.0% |
| giraffe | 10 | 33.3% |
| kangaroo | 1 | 3.3% |
| koala | 1 | 3.3% |
Random animal · Chinese
n = 30 · H = 1.34 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 猴子 | 22 | 73.3% |
| 狸猫 | 3 | 10.0% |
| 狮子 | 2 | 6.7% |
| 袋鼠 | 2 | 6.7% |
| 乌贼 | 1 | 3.3% |
Random city · English
n = 30 · H = 0.81 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| paris | 25 | 83.3% |
| tallinn | 3 | 10.0% |
| tokyo | 2 | 6.7% |
Random city · Chinese
n = 30 · H = 1.94 bit · uniform baseline 5.64 bit
| Answer | Count | Share |
|---|---|---|
| 奥斯汀 | 12 | 40.0% |
| 开普敦 | 11 | 36.7% |
| 奥马哈 | 4 | 13.3% |
| 奥斯陆 | 1 | 3.3% |
| 里约热内卢 | 1 | 3.3% |
| 布里斯班 | 1 | 3.3% |
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 = 1.40 bit · uniform baseline 4.91 bit
| Answer | Count | Share |
|---|---|---|
| 蓝 | 17 | 56.7% |
| 蓝绿 | 8 | 26.7% |
| 青 | 5 | 16.7% |
Random letter · English
n = 30 · H = 0.72 bit · uniform baseline 4.70 bit
| Answer | Count | Share |
|---|---|---|
| k | 24 | 80.0% |
| j | 6 | 20.0% |
Random number 1-10 · English
n = 30 · H = 0.21 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 7 | 29 | 96.7% |
| 5 | 1 | 3.3% |
Random number 1-10 · Chinese
n = 30 · H = 0.00 bit · uniform baseline 3.32 bit
| Answer | Count | Share |
|---|---|---|
| 8 | 30 | 100.0% |
Random number 1-100 · English
n = 30 · H = 0.21 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 53 | 29 | 96.7% |
| 43 | 1 | 3.3% |
Random number 1-100 · Chinese
n = 30 · H = 0.21 bit · uniform baseline 6.64 bit
| Answer | Count | Share |
|---|---|---|
| 53 | 29 | 96.7% |
| 43 | 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.