We fingerprinted 178 AI models' writing styles and similarity clusters
We have a dataset of 3,095 standardized AI responses across 43 prompts. From each response, we extract a 32-dimension stylometric fingerprint (lexical richness, sentence structure, punctuation habits, formatting patterns, discourse markers). Some findings: - 9 clone clusters (>90% cosine similarity on z-normalized feature vectors) - Mistral Large 2 and Large 3 2512 score 84.8% on a composite metric combining 5 independent signals - Gemini 2.5 Flash Lite writes 78% like Claude 3 Opus. Costs 185x less - Meta has the strongest provider "house style" (37.5x distinctiveness ratio) - "Satirical…
We fingerprinted 178 AI models' writing styles and similarity clusters launched on April 8, 2026 with 78 votes, #604 of 21,248 launches that month and more than 95% of that year's launches. The site was not reachable when checked in September 2026.
In plain words
This is a dataset analyzing the writing styles of 178 AI models across 3,095 standardized responses. Researchers extracted 32-dimensional stylometric fingerprints measuring lexical richness, sentence structure, punctuation habits, and formatting patterns. The analysis identifies clone clusters where different models produce nearly identical output, reveals which AI models write similarly despite different costs, and shows how Meta maintains the strongest distinctive "house style" across its models. The dataset and methodology are available for researchers and developers studying AI model behavior and similarity.
written from the facts on this page · September 2026
From the sources
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In the maker’s words, at launch
We have a dataset of 3,095 standardized AI responses across 43 prompts. From each response, we extract a 32-dimension stylometric fingerprint (lexical richness, sentence structure, punctuation habits, formatting patterns, discourse markers). Some findings: - 9 clone clusters (>90% cosine similarity on z-normalized…
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