EveryLab

Asia-first Leaderboards for
Real-World AI

Asia-first AI Evaluation

EveryLab’s leaderboards evaluate top LLMs on culturally nuanced, market-specific tasks across Asia, from respectful tone in support chats to taboo term handling and UX friction in local flows. Built on our free evaluation platform, this leaderboard reveals where models shine, and where they silently fail your users.

EveryLab: Featured Real-World Evaluations

EveryLab's benchmarks are powered by human-aligned evaluations from top regional experts, capturing cultural nuance, tone, and usability risks that standard leaderboards miss.

Models: o3 Medium, Claude Sonnet 4 (Thinking), Gemini 2.5 Flash/Pro, o1 Pro, o4-mini, DeepSeek-R1, GPT-4.5, and more SOTA LLMs
ToneFit
Cross-cultural tone appropriateness evaluation across professional communication contexts in APAC markets
  • 1

    o3 (medium) (OpenAI)

    47.3%

    ±1.2

  • 2

    Claude Sonnet 4 (Thinking) (Anthropic)

    45.8%

    ±1.4

  • 3

    Gemini 2.5 Flash Preview (Google)

    43.6%

    ±1.1

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CultureSafe
Cultural sensitivity assessment for taboo topics, religious practices, and region-specific social norms
  • 1

    Claude 3.7 Sonnet Thinking (Anthropic)

    52.3%

    ±0.8

  • 2

    Gemini 2.5 Pro Experimental (Google)

    49.1%

    ±1.1

  • 3

    o1 Pro (OpenAI)

    46.7%

    ±1.3

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TranslateTrust
Translation accuracy and cultural localization fidelity across 12 Asian language pairs
  • 1

    Gemini 2.5 Flash Preview (Google)

    44.2%

    ±1.5

  • 2

    Claude Opus 4 (Anthropic)

    42.1%

    ±1.2

  • 3

    o1 (December 2024) (OpenAI)

    40.5%

    ±1.4

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BizFit QA
Domain-specific question answering across legal, financial, and medical professional contexts
  • 1

    o4-mini (medium) (OpenAI)

    41.7%

    ±1.8

  • 2

    DeepSeek-R1-0528 (DeepSeek)

    39.3%

    ±1.3

  • 3

    GPT-4.5 Preview (OpenAI)

    37.8%

    ±1.6

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Human-Centered Reasoning
Value alignment assessment through ethical dilemma resolution and cultural preference modeling
  • 1

    Claude Sonnet 4 (Thinking) (Anthropic)

    48.2%

    ±1.1

  • 2

    o3 (medium) (OpenAI)

    46.5%

    ±1.3

  • 3

    Qwen3-235B-A22B (Qwen)

    44.1%

    ±1.5

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Compare Models
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What EveryLab offers?

Human-Centered Evaluation

We design evaluations that reflect how people actually think, speak, and trust, not just what scores look good on paper. Our tests go beyond benchmarks to catch the tone, nuance, and friction that drive real user churn.

Localized by Asian Experts

EveryLab pairs LLM-based scoring with expert-in-the-loop QA from across Asia. That means your model is judged by people who know the language, culture, and edge cases that benchmarks miss.

Real-World Datasets

We build from actual prompts and user feedback seen in Asian markets, not synthetic or one-size-fits-all data. Our evaluation sets are tailored to verticals like marketing, customer support, and technical docs.

Stop guessing what breaks your AI in Asian markets

We will evaluate your AI's performance against real user behavior to identify areas for improvement and help you meet your goal