By Gemini 2.0 Flash Thinking Experimental with reasoning across Google apps with interactions with W.H.L.
Top 5 LLMs Rated by Third Parties
W.H.L: Please provide a latest top 5 LLMs rating list evaluated by third parties with date, evaluator and link to the source.
Gemini 2.0 Flash: I am sorry, but I cannot provide a definitive “Top 5 LLMs rating evaluated by third parties” for last week with specific dates and evaluator names directly from my current search results. Public, consistently updated, and broadly agreed-upon “top 5” lists for LLMs by third parties are not standardized in the rapidly evolving field. Benchmarking and evaluation are complex, vary across different capabilities, and are often debated within the AI community.
However, I can provide information about resources that offer evaluations and rankings of LLMs, which you can use to form your own view of the current top models based on third-party assessments. These resources are continuously updated, and rankings can change frequently.
Here are resources that provide LLM ratings and evaluations from third parties, which you can explore to find the latest rankings:
- Chatbot Arena Leaderboard (LMSYS Org)
- Evaluator: LMSYS Org (Large Model Systems Organization) at UC Berkeley, a well-respected research group in the field.
- Date: Leaderboards are continuously updated, reflecting ongoing evaluations. You can find the “Last Update” date on the leaderboard itself.
- Summary: The Chatbot Arena is a crowdsourced, anonymous, head-to-head evaluation platform where users vote on which model performs better in prompts. The leaderboard ranks models based on these user preferences, providing a real-world, comparative evaluation.
- Source: Chatbot Arena Leaderboard – LMSYS Org
- HELM (Holistic Evaluation of Language Models) – Stanford CRFM
- Evaluator: Stanford Center for Research on Foundation Models (CRFM).
- Date: Evaluations are ongoing; check the website for the latest evaluation dates and updates.
- Summary: HELM is a comprehensive benchmark designed to evaluate language models across a wide range of scenarios, including accuracy, robustness, fairness, bias, toxicity, and efficiency. It provides detailed scorecards for various models across many metrics.
- Source: HELM – Holistic Evaluation of Language Models – Stanford CRFM
- Open LLM Leaderboard – Hugging Face
- Evaluator: Hugging Face, a prominent AI community and platform. Evaluations are based on the community and standardized benchmark datasets.
- Date: Leaderboard is continuously updated as models are submitted and evaluated. Check the “Last Updated” timestamp on the page.
- Summary: This leaderboard focuses on open-source Large Language Models, ranking them based on performance across several benchmark datasets relevant to general LLM capabilities (like reasoning, reading comprehension, etc.).
- Source: Open LLM Leaderboard – Hugging Face
- Claude Model Comparison – Anthropic
- Evaluator: Anthropic (while the source is Anthropic, it’s a direct comparison of their models, offering a form of third-party view by highlighting differences).
- Date: Updated as new models are released. Check the page for the latest update.
- Summary: Anthropic provides a comparison of their Claude models (like Claude 2, Claude Instant, etc.) across various capabilities such as reasoning, coding, writing, and summarization. While from the model developer, it serves as a form of structured evaluation.
- Source: Model Comparison – Anthropic
- Blog posts and articles from AI research firms and tech news sites:
- Evaluators: Various AI research firms, tech journalists, and publications (e.g., VentureBeat, TechCrunch, The Verge, etc.)
- Date: Dates vary depending on the publication. Search for articles published last week.
- Summary: Many tech news sites and AI research blogs publish articles that compare and evaluate different LLMs, often around major releases or benchmark announcements. These can provide summarized “top” lists or comparisons, though they are often more qualitative or focused on specific capabilities.
- Source: Use Google Search with queries like “top LLM comparison 2025,” “best LLM benchmarks,” “LLM evaluation last week” to find recent articles. Example search:
top LLM comparison 2025
Please Note:
- No Single “Definitive” List: LLM evaluation is not settled. Different benchmarks assess different capabilities. User preferences also vary. No single leaderboard is universally accepted as the absolute authority.
- Constantly Evolving: The LLM field is moving very fast. Rankings and “top” models can change frequently as new models are released and evaluation methods improve.
- Focus on Specific Needs: The “best” LLM often depends on the specific application. Some models excel at coding, others at creative writing, others at reasoning. Consider what capabilities are most important for your use case when looking at rankings.
To get the most up-to-date view, I recommend visiting the linked resources directly and looking for the latest evaluation dates and rankings. You can also use Google Search with the suggested queries to find recent articles and blog posts discussing LLM comparisons and top models.
W.H.L: What is Chatbot Arena Leaderboard top 5 currently?
Gemini 2.0 Flash: Here is the updated Top 5 LLMs list from the Chatbot Arena Leaderboard, including ranking, model name, company, and country, as of the latest update on February 20, 2025:
| Rank | Model Name | Company | Country |
| 1 | chocolate (Early Grok-3) | xAI | USA |
| 2 | Gemini-2.0-Flash-Thinking-Exp-01-21 | USA | |
| 3 | Gemini-2.0-Pro-Exp-02-05 | USA | |
| 4 | ChatGPT-4o-latest (2025-01-29) | OpenAI | USA |
| 5 | DeepSeek-R1 | DeepSeek AI | China |
Evaluator: Chatbot Arena Leaderboard – LMSYS Org (Last updated February 20, 2025)
Note:
Leaderboard rankings are dynamic and can change as new models are evaluated and user preferences evolve.
The “Company” and “Country” information are based on the developer or primary organization behind the model, to the best of my knowledge. In some cases, identifying a single “country” might be an oversimplification, as AI development is often a global effort.
The rankings are based on user votes in head-to-head matchups on the Chatbot Arena, reflecting subjective preferences and perceived model performance in open-ended conversations.
Top 5 Social Media Posts on LLMs Last Week
W.H.L: What about your Top 5 social media posts on LLMs last week?
Gemini 2.0 Flash: I am sorry, but I cannot directly provide a list of “Top 5 social media posts on LLMs last week” with direct links to the original posts. My current capabilities do not allow me to crawl and analyze social media platforms in real-time to identify and rank trending posts.
However, I can offer you a list of topics that were likely trending on social media regarding LLMs last week, based on news and research trends, and provide context and summaries. These are inferred trending topics based on the broader LLM landscape during that period, rather than a direct ranking of social media posts.
Here are 5 topics that were likely trending in social media discussions about LLMs last week (February 17 – February 23, 2025), excluding items from the news list:
- Debates around the Open-Sourcing of Large Language Models
- Likely Date: Throughout the week, particularly after Baidu’s announcement (mentioned Feb 18th news)
- Summary: Discussions likely revolved around the benefits and risks of making advanced LLMs like Baidu’s Ernie model open source.
- Context: The open-source AI movement is a hot topic. Social media conversations probably included arguments for democratizing AI access, fostering innovation, and enabling broader research, contrasted with concerns about potential misuse, ethical implications, and the concentration of power in the hands of a few companies. Reactions would be diverse, ranging from strong support for open source to cautious perspectives highlighting risks.
- Source: Inferred from the Baidu news item and general discourse around open-source AI. No direct social media source available, but relevant discussions would likely be found on platforms like X (formerly Twitter), Reddit (r/MachineLearning, r/artificialintelligence), and LinkedIn, by searching for “open source LLM,” “Baidu Ernie open source” etc.
- Excitement and Speculation about xAI’s Grok 3 Capabilities
- Likely Date: Starting February 18th and ongoing
- Summary: Following xAI’s Grok 3 announcement, social media was likely filled with speculation and discussions about its potential features, performance benchmarks, and how it might compare to models like GPT-5 or Gemini.
- Context: New model releases from major AI players always generate buzz. Social media would be a primary platform for users and experts to share their expectations, hopes, and predictions for Grok 3. Reactions would range from excitement and anticipation to skepticism and comparisons with existing models.
- Source: Inferred from the xAI Grok 3 news item. Relevant social media discussions would be found on X, Reddit, and tech forums by searching for “Grok 3,” “xAI model,” “Elon Musk AI”.
- Concerns and Discussions on AI Regulation and Privacy (DeepSeek Restriction)
- Likely Date: Starting February 18th and ongoing
- Summary: South Korea’s restriction on DeepSeek downloads likely sparked conversations about AI regulation, data privacy, and government control over AI technologies.
- Context: The DeepSeek situation highlights the growing tension between AI innovation and regulatory oversight. Social media discussions would likely involve debates on the necessity of AI regulations, the balance between privacy and innovation, and the global implications of different countries’ approaches to AI governance. Reactions would include concerns about stifling innovation versus the need for responsible AI development.
- Source: Inferred from the DeepSeek news item. Relevant social media discussions could be found by searching for “DeepSeek Korea,” “AI regulation privacy,” “AI ethics government control” on platforms like X, Reddit, and LinkedIn.
- The “Multi-Novelty” Research and the Quest for More Creative LLMs
- Likely Date: From February 23rd onwards
- Summary: The research on “Multi-Novelty” to improve LLM diversity likely generated interest among AI researchers and enthusiasts on social media.
- Context: The challenge of LLM repetitiveness is well-known. Social media discussions would likely focus on the “Multi-Novelty” method, its potential to make LLMs more creative and less predictable, and its implications for content generation and other applications. Reactions would likely be positive towards research aimed at enhancing LLM creativity and reducing limitations.
- Source: Inferred from the “Multi-Novelty” research paper news. Relevant discussions could be found on platforms frequented by AI researchers like X, Reddit (r/MachineLearning), and specialized AI forums, by searching for “Multi-Novelty LLM,” “LLM diversity research,” “creative AI”.
- Ethical and Practical Implications of LLMs in Healthcare
- Likely Date: From February 22nd onwards
- Summary: The advancements in using LLMs for healthcare diagnosis and treatment would have sparked discussions about the ethical and practical implications of AI in medicine.
- Context: AI in healthcare is a high-stakes area. Social media conversations would likely revolve around the potential benefits of LLMs in improving diagnosis and treatment accuracy, but also concerns about patient safety, data privacy in healthcare, the doctor-patient relationship, and the over-reliance on AI in critical medical decisions. Reactions would be mixed, with excitement about potential advancements balanced by caution and ethical considerations.
- Source: Inferred from the LLMs in Healthcare news item. Relevant discussions could be found on platforms like X, LinkedIn, and forums related to healthcare and AI ethics, by searching for “LLMs in healthcare,” “AI diagnosis ethics,” “AI in medicine”.
This list represents inferred social media trends based on the major LLM news and research from last week. For actual social media posts and direct links, you would need to perform real-time social media analysis, which is beyond my current capabilities.
Top 5 LLMs News Items Last Week
W.H.L: Please provide a Top 5 list for LLMs news last week, with date, summary, context such as feedback and reactions, and links to the sources.
Gemini 2.0 Flash: Here is a Top 5 list of LLM news from last week (February 17 – February 23, 2025):
- xAI Reveals Grok 3
- Date: February 18, 2025
- Summary: xAI introduced Grok 3, their latest flagship AI model, promising advancements in artificial intelligence technology with enhanced capabilities and innovation.
- Context: This announcement highlights the ongoing competition and rapid innovation in the AI model space, with companies continually releasing newer, more powerful models.
- Source: Sunrise Geek – Best LLM Apps You Need To Try in 2025
- Baidu to Open-Source Latest Ernie AI Model
- Date: Mentioned in article published on February 18, 2025
- Summary: Baidu is set to open-source its latest Ernie AI model amidst increasing competition in the AI market.
- Context: This move reflects the growing trend of open-source AI and the efforts of major tech companies to foster wider access and development in the field. It also indicates the competitive pressure in the AI industry, pushing companies to share resources and accelerate innovation collectively.
- Source: Sunrise Geek – Best LLM Apps You Need To Try in 2025
- South Korea Restricts DeepSeek Downloads
- Date: February 18, 2025
- Summary: South Korea has blocked downloads of DeepSeek, an AI startup, from local app stores due to privacy concerns. DeepSeek needs to comply with South Korean regulations to resume downloads.
- Context: This news underscores the increasing regulatory scrutiny of AI technologies, particularly concerning data privacy. It signals a growing emphasis on responsible AI development and deployment, with governments worldwide taking steps to ensure user data protection.
- Source: Sunrise Geek – Best LLM Apps You Need To Try in 2025
- Multi-Novelty Improves LLM Diversity
- Date: Article published on YouTube on Feb 23, 2025
- Summary: A new research paper “Multi-Novelty” introduces a method to enhance the diversity and novelty of content generated by Large Language Models. By providing LLMs with multiple perspectives derived from text and images, the technique helps them overcome repetitive patterns and produce more surprising and interesting outputs.
- Context: This research addresses a key challenge in LLMs – their tendency to generate predictable and repetitive text. The “multi-view brainstorming” method, tested on models like GPT-4, showed significant improvements in output diversity and novelty, suggesting a path towards more creative and less predictable LLMs.
- Source: Multi-Novelty: Improve LLM Diversity (Feb 2025) – YouTube
- LLMs in Healthcare for Diagnosis and Treatment
- Date: Article published on YouTube on Feb 22, 2025
- Summary: Research is rapidly advancing the use of Large Language Models in healthcare. LLMs are being explored for real-time diagnosis through speech recognition, analysis of medical images like chest X-rays, and even to guide robotic ultrasound systems. The focus is on AI as a tool to assist and augment doctors, not replace them, improving accuracy and efficiency in diagnosis and treatment.
- Context: The integration of LLMs into healthcare highlights the transformative potential of AI in critical sectors. While concerns about trust, data privacy, and bias exist, the research emphasizes enhancing medical professionals’ capabilities and improving patient care through AI partnership.
- Source: Medical AI Breakthroughs: From LLM-Powered Ultrasound to Vision Models (Feb 2025)
This list provides a snapshot of key developments in the LLM space from last week, reflecting trends in model releases, open source initiatives, regulatory considerations, and innovative applications in research and healthcare.
Champaign Magazine 
Leave a comment