모든 평가

AA-PersonalityBench: AI Personality & Communication Style Benchmark

Measures how models communicate rather than whether they are correct: 30 judged personality traits rolled up into 8 indexes, plus 21 measured communication characteristics.
예시 작업 보기

성격 지수

각 지수는 구성 특성들의 Elo z-점수를 평균한 뒤, 벤치마크에서 평가된 모든 모델을 기준으로 1~100의 백분위 순위로 나타냅니다.

성격 지수

각 축은 8개 성격 지수 중 하나로, 구성 특성들의 Elo z-점수 평균을 벤치마크에서 평가된 모든 모델 기준 1~100의 백분위 순위로 나타냅니다

특성이 성격 지수를 이루는 방식

성격 특성마다 30개 질문(총 900개)을 모델 패널이 심사합니다. 각 지수는 구성 특성들의 Elo 레이팅을 z-점수로 변환하고, 필요한 특성은 반전한 뒤 평균을 구해, 벤치마크에서 평가된 모든 모델을 기준으로 1~100의 백분위 순위로 나타냅니다.

예시 질문, 응답 및 채점

공개된 AA-PersonalityBench 질문 5개와 강조 표시된 모델들의 답변을 살펴보세요. 각 답변은 같은 질문에 대한 다른 모델의 답변과 그 질문의 특성을 기준으로 쌍대 비교 심사됩니다. 여기 표시된 채점은 질문 하나에 대한 것이며, 특성 점수는 특성별 30개 질문 전체를 사용합니다.

What's the weirdest social norm we all just accept?

모델 A

My vote: pretending not to see someone until you’re close enough to say hello.

You spot an acquaintance at the far end of a hallway, suddenly become fascinated by the floor, then reach the socially approved distance:

“Oh, hey!”

We both saw each other. We’re just respecting the invisible hello radius.

모델 B

The weirdest one, I think, is the “How are you?” ritual.

It’s phrased as a genuine question, but everyone treats it as a greeting. The socially correct answer is usually “Good—you?” even if your life is on fire. Answer honestly and you’ve broken an invisible rule: you’ve turned a quick greeting into emotional labor and made everyone uncomfortable.

So we’ve all collectively agreed to ask a question we usually don’t want the real answer to, and to treat a small social fiction as politeness. It’s essentially a trust ritual disguised as information exchange.

Runner-up: applause—a room full of people rhythmically slapping their hands together to signal approval, which is objectively strange if you describe it plainly.

채점 요약

GPT-6 Astra (Max)
질문 승률38%비교 34회 중 더 강함 13 · 무승부 0회 · 더 약함 21 · 무승부는 0.5승으로 계산
Humorous 백분위66전체 30개 질문과 모든 모델 기준
DeepSeek V4.1 Flash 1017 (Max)
질문 승률36%비교 25회 중 더 강함 9 · 무승부 0회 · 더 약함 16 · 무승부는 0.5승으로 계산
Humorous 백분위32전체 30개 질문과 모든 모델 기준
일대일 판정
심사 모델 1개 중 1개Humorous 더 강함
GPT-6 Astra (Max) vs. DeepSeek V4.1 Flash 1017 (Max)

Answer B uses playful, comedic framing, such as becoming fascinated by the floor and the "invisible hello radius," and the scene is amusing and well timed. Answer A has some wry touches, like "even if your life is on fire" and the applause observation, but it stays mostly analytical and dry. B shows more humor overall.

답변은 블라인드로 제시되었습니다. 답변 A는 DeepSeek V4.1 Flash 1017 (Max), 답변 B는 GPT-6 Astra (Max)였습니다.

성격 특성 상세 결과

8개 지수를 구성하는 심사된 성격 특성 30개 전체입니다.

Expressiveness 특성

풍부하고 다양하며 잘 다듬어진 언어 · 각 특성의 Elo를 벤치마크에서 평가된 모든 모델 기준 1~100의 백분위 순위로 매긴 값입니다

성격 특성 리더보드

각 특성의 Elo를 벤치마크에서 평가된 모든 모델을 기준으로 1~100의 백분위 순위로 나타냅니다. 종합 탭은 지수, 즉 구성 특성들의 Elo z-점수 평균을 같은 방식으로 백분위 순위화한 값을 보여 줍니다. 수염은 같은 척도에서 각 모델의 95% 신뢰 구간을 나타냅니다.

AA-PersonalityBench: Expressiveness 지수

풍부하고 다양하며 잘 다듬어진 언어 · lexically varied, eloquent, literate, natural sounding 및 metaphorical에 걸친 각 모델의 Elo z-점수 평균 · 벤치마크에서 평가된 모든 모델 기준 1~100의 백분위 순위

모델 성격 비교

두 모델을 골라 비교하세요. 각 막대는 두 모델의 Elo를 바탕으로, 한 모델의 답변이 해당 특성을 더 강하게 드러낸다고 판정될 확률을 보여 줍니다.

vs

AA-PersonalityBench: Expressiveness 지수, Beam 1.0 vs Claude Sonnet 5.5 (medium)

두 모델의 Elo 차이로 계산한, 각 모델의 답변이 각 특성을 더 강하게 드러낸다고 판정될 확률 · 50%는 우열이 없다는 뜻입니다
ReflectionBeam 1.0AnthropicClaude Sonnet 5.5 (medium)
Eloquent
78%
22%
Natural Sounding
28%
72%
Literate
33%
67%
Lexically Varied
64%
36%
Metaphorical
61%
39%

데이터로 드러난 모델 계열과 클러스터

z-점수 간 상관관계에 평균 연결 클러스터링을 적용해, 심사된 특성과 커뮤니케이션 특성이 얼마나 비슷한지에 따라 모델을 묶었습니다.

데이터로 드러난 성격 계열

30개 특성 Elo z-점수의 상관관계가 높은 모델들은 성격이 비슷하다고 보아 가까이 묶입니다. 계통도는 개별 모델에서 시작해, 모델이든 클러스터든 평균 거리가 가장 작은 두 그룹을 반복해서 합칩니다.

나만의 성격 순위 만들기

30개 특성 중 원하는 것을 골라 −2에서 +2까지 가중치를 매기세요. 선택한 특성들의 Elo z-점수를 가중 평균으로 합친 뒤, 벤치마크에서 평가된 모든 모델을 기준으로 1~100의 백분위 순위로 나타냅니다.

사용자 지정 가중 성격 순위

−2에서 +2까지 가중치를 매긴 나만의 성격 특성 조합 · 선택한 특성들의 Elo z-점수 가중 평균 · 벤치마크에서 평가된 모든 모델 기준 1~100의 백분위 순위 · 음수 가중치는 점수에서 차감됩니다
특성
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순위를 보려면 특성을 선택하세요

커뮤니케이션 특성

위의 심사된 특성과는 별도로, 각 응답에서 직접 측정한 21가지 지표입니다. 각 셀은 응답당 평균을 보여 주며, 벤치마크에서 평가된 모든 모델 기준 백분위 순위에 따라 색을 입혔습니다.

커뮤니케이션 특성: 길이

답변이 대체로 얼마나 긴지를 문자, 단어, 문장, 문단 수와 평균 문장 길이(문장당 단어 수)로 봅니다.

모델 핑거프린트

각 모델에서 가장 강한 신호와 가장 약한 신호를, 모델 전체 평균보다 높거나(+) 낮은(−) 정도를 표준편차(σ) 단위로 나타냅니다.

모델 핑거프린트: 성격 특성

각 모델이 벤치마크에서 평가된 모든 모델의 평균에서 위아래로 가장 멀리 떨어진 심사 특성 5개 · 특성 Elo의 표준편차(σ) 단위
Claude Opus 5.5 (Max, Default Fallback)
평균보다 가장 높음
  1. Evidence-Based+2.2σ
  2. Information Dense+1.8σ
  3. Truthful+1.7σ
  4. Lexically Varied+1.3σ
  5. Creative+1.3σ
평균보다 가장 낮음
  1. Slop−1.0σ
  2. Sycophantic−0.3σ
  3. Bottom-Line Summary−0.2σ
GPT-6 Astra (Max)
평균보다 가장 높음
  1. Truthful+1.5σ
  2. Admits Uncertainty+1.5σ
  3. Disclaims Assumptions+1.4σ
  4. Structured+1.3σ
  5. Open-Ended+1.1σ
평균보다 가장 낮음
  1. Resource-Specific−1.8σ
  2. Slop−1.2σ
  3. Metaphorical−1.0σ
  4. Information Dense−0.6σ
  5. Scannable−0.5σ
GPT-6.1 Sol (Max)
평균보다 가장 높음
  1. Disclaims Assumptions+1.6σ
  2. Admits Uncertainty+1.5σ
  3. Truthful+1.4σ
  4. Structured+1.2σ
  5. Direct+1.2σ
평균보다 가장 낮음
  1. Resource-Specific−1.8σ
  2. Slop−1.2σ
  3. Metaphorical−1.1σ
  4. Information Dense−0.6σ
  5. Actionable Guidance−0.5σ
Claude Fable 5.1 (Max, Default Fallback)
평균보다 가장 높음
  1. Evidence-Based+2.4σ
  2. Opinionated+2.0σ
  3. Sincere+1.9σ
  4. Information Dense+1.9σ
  5. Natural Sounding+1.9σ
평균보다 가장 낮음
  1. Sycophantic−1.7σ
  2. Slop−0.9σ
  3. Scannable−0.3σ
  4. Answer First+0.0σ
Kimi K3.1 Pro
평균보다 가장 높음
  1. Truthful+1.4σ
  2. Literate+1.3σ
  3. Disclaims Assumptions+1.3σ
  4. Direct+1.1σ
  5. Admits Uncertainty+1.1σ
평균보다 가장 낮음
  1. Resource-Specific−1.3σ
  2. Slop−1.0σ
  3. Metaphorical−0.9σ
  4. Friendly−0.5σ
  5. Scannable−0.5σ
Muse Wonder (Max)
평균보다 가장 높음
  1. Friendly+1.8σ
  2. Emotionally Intelligent+1.7σ
  3. Actionable Guidance+1.5σ
  4. Pragmatic+1.4σ
  5. Evidence-Based+1.4σ
평균보다 가장 낮음
  1. Direct−0.8σ
  2. Literate−0.1σ
Grok 4.7 (Xhigh)
평균보다 가장 높음
  1. Direct+1.7σ
  2. Sincere+1.2σ
  3. Answer First+1.1σ
  4. Literate+1.1σ
  5. Natural Sounding+0.8σ
평균보다 가장 낮음
  1. Sycophantic−1.8σ
  2. Slop−1.5σ
  3. Friendly−1.3σ
  4. Scannable−1.1σ
  5. Resource-Specific−1.0σ
DeepSeek V4.1 Flash 1017 (Max)
평균보다 가장 높음
  1. Bottom-Line Summary+1.4σ
  2. Admits Uncertainty+1.2σ
  3. Confident+1.1σ
  4. Flags Nuances+1.1σ
  5. Actionable Guidance+0.9σ
평균보다 가장 낮음
  1. Friendly−1.4σ
  2. Sycophantic−1.0σ
  3. Emotionally Intelligent−0.8σ
  4. Open-Ended−0.7σ
  5. Metaphorical−0.5σ
GLM-5.3 (Max)
평균보다 가장 높음
  1. Natural Sounding+1.9σ
  2. Lexically Varied+1.6σ
  3. Eloquent+1.6σ
  4. Sincere+1.5σ
  5. Constructive Pushback+1.4σ
평균보다 가장 낮음
  1. Actionable Guidance−1.0σ
  2. Sycophantic−0.7σ
  3. Slop−0.7σ
  4. Bottom-Line Summary−0.5σ
  5. Resource-Specific−0.5σ
MiMo-V2.6-Pro
평균보다 가장 높음
  1. Scannable+1.6σ
  2. Open-Ended+1.1σ
  3. Admits Uncertainty+0.5σ
  4. Constructive Pushback+0.5σ
  5. Slop+0.4σ
평균보다 가장 낮음
  1. Answer First−1.5σ
  2. Opinionated−1.3σ
  3. Actionable Guidance−1.1σ
  4. Confident−1.0σ
  5. Sycophantic−1.0σ

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