AA-PersonalityBench Ranks Model Personality and Communication Style
The non-obvious insight is that correctness alone no longer separates models; style metrics like Slop and Conviction now offer a measurable way to pick a model for tone-sensitive use-cases such as legal drafting or creative writing. Teams building user-facing products can use the eight indexes to shortlist models matching their brand voice. The data covers Chinese models like GLM-5.3, DeepSeek V4.1 Flash and Qwen3.8 27B alongside Western ones, making direct stylistic comparison across the two ecosystems possible.
Artificial Analysis launched AA-PersonalityBench, a benchmark measuring language models across 30 personality traits and 21 communication characteristics. The benchmark evaluates responses to 900 curated questions, using LLM judges for pairwise comparison of subjective traits and programmatic calculation of objective characteristics. Traits roll up into eight Personality Indexes, including Expressiveness, Warmth, Conviction, Imagination and Slop, with Claude Fable 5.1 and GLM-5.3 leading Expressiveness. On communication style, Qwen3.8 27B averages about 1,030 words per response versus 270 for GPT-6 Luna, and GLM-5.3 averages 7 em dashes per response while Claude Opus 5.5 almost never uses one.
Announcing AA-PersonalityBench, our new benchmark of the personality of language models across 30 traits and their communication style across 21 characteristics
Two models can give equally correct answers and still feel very different to use. AA-PersonalityBench measures those differences so people can understand which to use in different use-cases. Some use-cases like creative writing might demand imagination, while legal use-cases might demand directness. We evaluate models’ answers to 900 curated questions to judge subjective Personality Traits and programmatic means to calculate objective Communication Characteristics.
Personality Traits & Indexes. There are 30 personality traits (e.g., eloquent, pragmatic, sycophantic) which we roll up into eight aggregated Personality Indexes: Expressiveness, Organization, Informativeness, Transparency, Warmth, Conviction, Imagination and Slop. Each trait has a set of 30 dedicated questions and models’ answers are compared pairwise by a panel of LLM judges. We then z-score and percentile rank the trait and personality Elos.
Models with the strongest representation across the 8 Personality Indexes: ➤ Expressiveness: Claude Fable 5.1, GLM-5.3, GLM-5.3-Flash ➤ Organization: DeepSeek V4.1 Flash, Step 5 Preview, Inkling ➤ Informativeness: Muse Spark 1.3, Claude Fable 5.1, Muse Wonder, Claude Opus 5.5 ➤ Transparency: Claude Sonnet 5.5, Claude Fable 5.1, GPT-6 Astra ➤ Warmth: Muse Wonder, Muse Spark 1.3, Claude Fable 5.1 ➤ Conviction: Claude Fable 5.1, DeepSeek V4.1 Flash, Grok 4.7 ➤ Imagination: Muse Spark 1.3, Claude Opus 5.5, GLM-5.3 ➤ Slop: Llama 4 Maverick, GPT-4o, K2 Horizon
Communication Characteristics. There are 21 communication characteristics (e.g., average sentence length, emoji use, em dash usage) which we group into four categories: length, structure, punctuation, and emphasis. We compute these characteristics programmatically across all model responses. ➤ Length: Qwen3.8 27B averages about 1,030 words per response, nearly four times GPT-6 Luna’s 270 ➤ Structure: Nemotron 3 Ultra averages nearly 3 tables per response, while most models rarely use one ➤ Punctuation: GLM-5.3 averages 7 em dashes per response, while Claude Opus 5.5, Sonnet 5.5 and Haiku 5.5 almost never use one ➤ Emphasis: K2 Horizon averages over 2 emoji per response, while most models almost never use one
