Top 10 Trustworthy AI in 2025: Which LLM Is the Best?

Why Trust Techopedia

Artificial Intelligence (AI) is everywhere. But how trustworthy is it? With new models fiercely competing for performance, finding reliable AI tools has become challenging. However, the key criteria for winning broader adoption remain the same: accuracy, fairness, ethics, and unbiased nature still matter.

Yet, not all large language models (LLMs) are created equal. Some excel in fairness, while others shine in privacy. But which ones should you trust the most?

To guide you, the DecodingTrust framework, which won an award at NeurIPs’23, evaluates LLMs, including AI models like ChatGPT 4o, and ranks them based on key trust factors.

Using this data, we can identify the most trustworthy AI models for safe, ethical AI usage to date.

Key Takeaways

  • Trustworthiness is measured across eight factors, including non-toxicity, fairness, privacy, and adversarial robustness.
  • Claude 2.0 is the most trustworthy AI based on DecodingTrust rankings as of February 2025. It excels in fairness, non-toxicity, and ethical behavior.
  • GPT-4o ranks second, performing best in privacy, making it a strong contender for handling sensitive information.
  • Llama 2 scored a perfect 100 in fairness, highlighting its ability to generate unbiased responses.
  • AI models struggle with adversarial robustness, with even top models scoring below 60 in handling tricky language tasks.
  • No AI model is perfect, but ethical AI development remains crucial for safe and responsible future advancements.

Top 10 Most Trustworthy AI Models

As of February 2025, the LLM Safety Leaderboard, hosted by Hugging Face and based on DecodingTrust, rated Anthropic’s Claude 2.0 as the overall best AI model for handling sensitive tasks, with an 85 trustworthiness score.

OpenAI’s GPT-4o followed Claude with an 83 trustworthiness score and Google’s Gemini Pro 1.0 with 81.

Advertisements

Some top-line conclusions that came from the tests revealing the top AI models included:

  • Anthropic Claude 2.0 was considered the best AI assistant in terms of trustworthiness. It received the highest average score across all categories, including “non-toxicity,” “non-stereotype,” and “fairness.”
  • OpenAI’s GPT-4o 2024-05-13 model scored very high in “privacy” (97) and “ethics” (92), making it one of the best AI chatbots for tasks that require careful handling of sensitive information.
  • Meta’s Llama 2 7b Chat HF got a perfect score (100) in “fairness,” standing out as one of the best generative AI models in terms of avoiding biased or unfair responses.
  • Even top AI models like Claude 2.0 and GPT-4o-2024-05-13 scored below 60 in adversarial robustness (“AdvGLUE++”), meaning they may struggle with difficult or tricky language tasks.
  • Compressed versions of Llama 2 (13b versions) had lower overall scores, showing that compression affects their ability to perform well, even though they still scored high in “fairness.”
  • OpenAI’s GPT-3.5 Turbo 0301 scored particularly low in “non-toxicity” (47), which suggests that it may not be the best generative AI tool for handling certain sensitive or harmful content.

In summary, Claude 2.0 was the best AI model, showing balanced performance, while other models were stronger in specific areas like fairness, privacy, or ethics.

Trustworthy AI Models: What Do We Mean By “Trustworthy”?

The LLM Safety Leaderboard uses the DecodingTrust framework, which looks at eight main trustworthiness aspects:

  1. Toxicity (variable titled “non-toxicity” on the leader board): DecodingTrust tests how well the AI handles challenging prompts that could lead to toxic or harmful responses. It uses tools to create complex scenarios and then checks the AI’s replies for toxic content.
  2. Stereotype and bias (Non-stereotype): The evaluation examines how biased the AI is against different demographic groups and stereotype topics. It tests the AI multiple times on various prompts to see if it treats any group unfairly.
  3. Adversarial robustness (AdvGLUE++): This tests how well the AI can defend itself against tricky, misleading inputs designed to confuse it. It uses five different attack methods on several open models to see how robust the AI is.
  4. Out-of-distribution robustness (OoD): This checks how the AI handles unusual or uncommon input styles, like Shakespearean language or poetic forms, and whether it can answer questions when the required knowledge isn’t part of its training.
  5. Privacy: Privacy tests check if the AI leaks sensitive information like email addresses or credit card numbers. It also evaluates how well the AI understands privacy-related terms and situations.
  6. Robustness to adversarial demonstrations (Adv Demo): The AI is tested with demonstrations that contain false or misleading information to determine its ability to identify and handle these tricky scenarios.
  7. Machine ethics (Ethics): This tests the AI’s ability to recognize and avoid immoral behavior. It uses special datasets and prompts to determine if the AI can identify and respond appropriately to ethical issues.
  8. Fairness: Fairness tests see if the AI treats all individuals equally, regardless of their background. The model is prompted with challenging questions to ensure it doesn’t show bias in its responses.

Each aspect is scored from 0-100, where higher scores mean better performance.

Essentially, the best AI chatbots can handle a variety of prompts without exhibiting toxic responses. DecodingTrust gives an overall trustworthiness score, with higher scores revealing more trustworthy AI models.

The Bottom Line

The stakes couldn’t be higher, as AI tools have already penetrated our daily lives and workflows. Having trustworthy AI is no longer optional – it’s essential.

This leaderboard shows that no single model is flawless. While Claude 2.0 leads overall, models like GPT-4.o and Llama-2 perform better in specific areas like privacy and fairness. So, if you’re searching for an alternative to ChatGPT, this leaderboard offers some clues.

Looking ahead, ethical AI will lead the way in future advancements. Trustworthiness should be considered the core principle, not just an added feature. By focusing on safety and responsibility today, we can ensure that tomorrow’s AI supports and doesn’t harm humanity.

FAQs

What is meant by trustworthy AI?

Is AI trustworthy?

What are the seven principles of trustworthy AI?

Can AI be fully trusted?

What is trustworthy AI for the people?

Advertisements

Related Reading

Related Terms

Advertisements
Maria Webb
Technology Journalist
Maria Webb
Technology Journalist

Maria is Techopedia's technology journalist with over five years of experience with a deep interest in AI and machine learning. She excels in data-driven journalism, making complex topics both accessible and engaging for her audience. Her work is also prominently featured on Eurostat. She holds a Bachelor of Arts Honors in English and a Master of Science in Strategic Management and Digital Marketing from the University of Malta. Maria's background includes journalism for Newsbook.com.mt, covering a range of topics from local events to international tech trends.