Welcome to our guide to the top-ranking Large Language Models (LLMs) and AI Chatbot tools currently available. 

In this article, we will review the top-performing Chatbot/LLMs that are widely available today. We’ll break down the leading firms developing these models (OpenAI, Anthropic, Google, etc.) and how they rank against one another. For each of our top companies, we’ll provide an overview of their leadership, top models, pros and cons, and what to watch from each. Finally, we’ll finish with some predictions of what we expect to see from the AI race in 2025. 

Use the links below to jump to specific sections of interest. 

AI Chatbot Rankings

Top 3 AI Chatbots and Models Overall by Intelligence and Reasoning

Best AI Chatbots by Category

Best AI Chatbot App

Top LLM Research Labs & Leading AI Chatbot Companies

1. OpenAI - ChatGPT
2. Anthropic - Claude
3. Google - Gemini
4. Alibaba - Qwen
5. Meta - Llama
6. DeepSeek - R1 & R3
7. xAI - Grok
8. Mistral - LeChat
9. Cohere
10. Perplexity

Honorable Mentions

Predictions for 2025

Conclusion

We write this with humility, knowing that the moment this list is published, it’s likely to be thrown asunder by a breakthrough in the artificial intelligence landscape. We saw this recently with DeepSeek’s rapid ascension and the launch of its breakthrough reasoning model. More recently, and to a lesser extent, we’ve seen it with Mistral’s launch of Le Chat. We expect more launches from companies like Antrhopic, xAI, and Google in 2025. 

A quick note on open vs. closed source models: the pace of innovation is accelerating, and it seems open source (DeepSeek, LLama, etc.) is also flexing its muscles against closed models, which opens up the potential for more universal and democratized AI adoption. Who will win that war is beyond the scope of this article. However, we’ve tried to cover open and closed-source models equally throughout. 

AI Chatbot Rankings

Ranking chatbots is marginally subjective, as each use case or individual user preferences will favor one model over another. That said, some widely accepted measurements exist for model intelligence and reasoning. Below, we share a summary of the current state-of-the-art models that are publicly available. 

You will notice that OpenAI, DeepSeek, and Google models are generally ranked at the top regarding demonstrated intelligence in reasoning, knowledge, and coding. As it relates to intelligence and reasoning, we see the top 3 models currently as follows:

Top 3 AI Chatbots and Models Overall by Intelligence and Reasoning  

• o1 by OpenAI
• R1 by DeepSeek
• Gemini 2.0 Pro Experimental by Google 

Other promising AI Chatbot’s (LLMs) include: 

• Claude by Anthropic
• Qwen by Alibaba 
• Llama by Meta
• MiniMax-Text-001 by MiniMax 

Best AI Chatbots by Category 

Based on performance, user adoption, and technological advancements, OpenAI’s ChatGPT stands out as a clear leader. However, OpenAI’s models are closed source and often have higher usage costs than other models; below, we give a quick breakdown of leading models based on other considerations such as them being open source, having the best cost, being the fastest or having a great app/user experience. 

Best Open Source AI Chatbots

• R1 by DeepSeek
• Llama 3.1 by Meta 

Best mix of cost/intelligence models / AI Chatbots

Generally, open-source models will be cheaper to run simply because anyone can spin up an instance and serve access to that model, which breeds competition and drives down costs. For that reason, open-source models will generally lead in the cost/intelligence category, and that is why you see DeepSeek and Llama at the top of the list. However, Google has done a good job of making its Gemini 2.0 Flash model low-cost, delivering a similar price per 1M output tokens of its open-source rivals. 

Best mix of cost/intelligence models 

• DeepSeek R1
• DeepSeek V3
• Gemini 2.0 Flash
• Llama 3.3 70B 

Fastest and Smartest AI Chatbots / Models 

AI model speed can be crucial for technical implementations, such as customer service interactions requiring rapid responses. For users of various chatbot tools, having a fast response is also crucial to the general user experience and adoption of AI tools. Slow tools and rate caps lead to users bouncing. 

This list is dominated by closed-model providers at the moment. We believe that shortly, optimized open-source versions of DeepSeek or future versions of Llama will likely compete with current leaders. 

Fastest and Smartest AI Chabots/Models on the market right now

• o3-mini by OpenAI 
• Gemini 2.0 Flash by Google 
• o1-mini by OpenAI

Adding to our earlier point, DeepSeek, while extremely smart, has shown high latency of late. That’s likely due to their meteoric rise in popularity, compounded by the lack of infrastructure that incumbents like Google or OpenAI possess. 

Best AI Chatbot App

User experience is largely subjective, but based on our usage of various AI chatbot apps, we find the following tools to be the most intuitive, user-friendly, flexible, and cost-effective: 

• Perplexity - Perplexity is a search-first AI tool aiming to displace Google search, however they’ve created a very user-friendly AI app and they allow users to test and use various models.  
• ChatGPT - OpenAI’s flagship offering, a great tool; however, the number of model choices and use cases can be confusing for users, and the limitations around each model type can be confusing, with web search or uploads available for some flavors and not for others.
• Claude - A very solid app with a clean and friendly user experience. They pioneered the use of artifacts to make generated content more engaging. The biggest downside is the models have not been updated recently and they’ve yet to launch an advanced reasoning model as of publication.  
• ChatLLM - A lesser-known tool, but it provides the flexibility to choose various models from OpenAI to Llama. And it comes at a low monthly cost with generous caps. We see ChatLLM as a great way to experiment and test across various models. 

How are LLM ranks changing day to day? 

If you’re looking to see who is currently the best at this very moment, you can check out pages that regularly update their chatbot leaderboards below: 

• Huggingface/LMAreana - Chatbot Arena LLM Leaderboard
• ArtificialAnalysis.ai - A great resource to compare LLMs which many of the charts in this article come from 
• Scale.com SEAL Leaderboard

Now, we look at search traffic as a proxy for user loyalty and adoption. 

Search Traffic Across Various Models 

While search traffic is not directly indicative of market position, it helps indicate the adoption trends for these various models as they grow in popularity or usage. The base assumption is more search signals equals increased usage. 

The table below shows the average monthly search volume over the last three months for the various AI research labs and their frontier models. We’ve removed large companies like Meta, Microsoft, and Amazon from the results, as much of their traffic is not necessarily AI-related.

ChatGPT remains the clear leader with orders of magnitude (40x) more search traffic than its AI-focused competitors. Indeed, to show the relative performance in search, we had to generate two charts, one with and one without ChatGPT included 

In this chart you can clearly see DeepSeek’s meteroic rise that came in late 2024 when R3 was launched.

This chart illustrates ChatGPT's scale when compared with its rivals.

The results are similar when we look at total visits from a source like similarweb which shows just how far ahead chatgpt is.

That said, some use cases favor Claude, for example, OpenRouter which offers “A unified interface for LLMs [with] Better prices, better uptime, no subscription,” shows that Claude is a favored tool for its developers, with a leading 25% usage share: 

Top LLM Research Labs & Leading AI Chatbot Companies

Below we attempt to rank the leading LLM research labs and chat providers, after we share the top 10 we cover “honorable mentions” which are firms that show promise to compete with the established incumbents but have limited penetration or are new entrants. 

1. OpenAI - ChatGPT

Overview

The clear category leader in AI. Tremendous market share with its GPT line of products and its models are almost always at the top of the charts in most competitive benchmarks. Closed source.

Leadership and Key Team Members

Key figures include Sam Altman and a team of researchers who continue to innovate in AI development. There have been significant leadership departures recently to start competing firms. 

Top Models

GPT-4o / o1 / o3-mini / o1pro

Pros

• Strong distribution and user adoption
• The brand is synonymous with AI for most of the population
• Strong technically, despite recent departures

Cons

• The corporate structure is messy, with a shift to a for-profit enterprise under assault
• A mass exodus by top AI leadership and talent has occurred 
• As the leader, they have a target on their back—from both competitors and regulators

What to Watch

OpenAI recently revealed plans to update and simplify its product roadmap. Reasoning models, including a $200/month pro subscription, are becoming more popular.

2. Anthropic - Claude

Overview

Anthropic’s Claude is known for its ethical approach to AI, prioritizing safety and nuanced conversation. It’s carving out a strong niche with its responsible innovation ethos. Many power users prefer Claude to OpenAI’s chatbot offerings. 

Leadership and Key Team Members

Led by a team of former OpenAI researchers, including Dario Amodei. Anthropic emphasizes transparency and a commitment to ethical AI practices.

Top Models

Claude 3.5 Sonnet, Claude Opus, Claude Haiku 

Pros

• Emphasis on ethical AI and safety
• High-quality conversational responses that some find more ‘empathetic’ 
• Strong and stable leadership team 

Cons

• Lower market penetration compared to larger industry players like OpenAI
• Early on their models were not as cost competitive
• They seem to have a lower launch cadence of new models, when compared to their competitors 

What to Watch

Recent reporting suggests that Anthropic will launch a new state-of-the-art model shortly that competes with or bests current leading models like OpenAI’s o1. 

3. Google - Gemini

Overview

Google’s Gemini series leverages deep search and data analytics integration with its Gsuite and other tools. Their flash models have become popular by offering lightning-fast responses and a vast knowledge base (context window).

Leadership and Key Team Members

Helmed by seasoned AI researchers, Gemini benefits from Google’s immense data infrastructure and research pedigree.

Top Models

Gemini 2.0 Flash, Gemini 2.0 Pro, Gemini Deep Research, Gemini Thinking Experimental, NotebookLM

Pros

• Seamless integration with Google’s ecosystem
• High-speed processing supported by large infrastructure 
• Robust data privacy and security measures for enterprise deployment 

Cons

• A closed ecosystem that can limit third-party integrations
• Complexity and model choices that may overwhelm casual users
• Low user adoption and risk that Google “over integrates” these tools to its existing offerings to show public investors Google AI tool adoption is higher than it is 

What to Watch

Google had an early lead in AI, but its internal bureaucracy and slow innovation cycle resulted in it ceding that lead to faster-moving rivals like OpenAI and Antrhopic. Google still has tremendous talent and infrastructure and will likely establish itself as a top player in AI in 2025 and beyond. 

4. Alibaba - Qwen

Overview

Alibaba’s Qwen is designed to serve commercial and consumer markets, emphasizing multilingual capabilities and regional customizations in Asia. Qwen 2.5 Max, its newest offering has shown tremendous promise. Alibaba also recently signed a contract with Apple to be the ‘brains’ behind Apple Intelligence in the Chinese market. 

Leadership and Key Team Members

Driven by a robust team of engineers and strategists, Qwen is supported by Alibaba’s vast technological resources.

Top Models

Qwen 2.5 Max, Qwen Lite, Qwen Pro, Qwen Enterprise

Pros

• Excellent performance in multilingual contexts
• Extensive support for regional markets
• Solid cloud infrastructure backing

Cons

• Limited global recognition outside of Asia
• Primarily optimized for Asian markets, affecting universal appeal and raising data concerns in the US 

What to Watch

Keep an eye on Qwen’s international expansion and improvements in global language support.

5. Meta - Llama

Overview

Meta’s Llama series strikes a balance between innovative open research and practical application, Zuckerberg and Meta are leading the charge on open-sourcing AI innovation, and rumors suggest these developments not only benefit the open-source community but have also helped make Meta’s ad machine more effective. 

Leadership and Key Team Members

Supported by Meta’s research labs and an active open-source community, Llama is constantly evolving.

Top Models

Llama 3.3 70B, Llama 3.3 405B

Pros

• Strong emphasis on open research and transparency
• Active community contributions leading to rapid improvements and branched innovations 
• Llama models and innovations have become a backbone for many open-source developments 

Cons

• By open-sourcing the model, Meta cannot directly monetize their AI developments. However, some see this as an advantage both for the company in building an ecosystem and for broader AI adoption 
• A new model needs to be developed soon to keep pace with closed-model rivals 

What to Watch

Expect further community-driven enhancements as Llama has established itself as the largest open-source model. 

6. DeepSeek - R1 & R3

https://www.deepseek.com/

We recently published an Article on DeepSeek’s R1 reasoning model, read it here. 

GitHub Repository: https://github.com/deepseek-ai

Overview

DeepSeek has emerged as a notable force in the open-source arena, rapidly gaining traction with its R1 and R3 models. Its reasoning model, in particular, garnered significant attention as it was one of the first models to openly display its chain of thought and deliver impressive results for users in real-life applications and on general intelligence benchmarks. 

Leadership and Key Team Members

DeepSeek’s core team consists primarily of young graduates from top Chinese universities like Peking University and Tsinghua University, recruited by founder Liang Wenfeng for their academic prowess rather than industry experience. Key members include former Microsoft Research Asia staff like Yu Wu, who leads AI alignment efforts, and “AI prodigy” Luo Fuli, reflecting a blend of academic rigor and unconventional talent acquisition. The team achieved breakthroughs in open-source AI models like DeepSeek-R1 through cost-effective optimization and pure reinforcement learning techniques, challenging established US competitors.

Top Models

R1 and R3

Pros

• Fully open source, encouraging community development and knowledge sharing
• Momentum in the open AI movement

Cons

• Still growing its commercial scalability
• They lacked the infrastructure to fully serve peak demand when their popularity skyrocketed
• There are data concerns for the DeepSeek.com hosted model which sends data to China, such a concern is not present for US-hosted flavors of the open source model 

What to Watch

Monitor DeepSeek’s roadmap as they continue pushing the boundaries of open-source AI development. It would be extremely impressive if they could continue to push the envelope in the AI race, especially given their relatively small financial backing and chip infrastructure when compared with companies like Meta, Google, OpenAI, and Antrhopic. 

7. xAI - Grok

Overview

Elon Musk’s xAI has grown in valuation rapidly over the last 12 months and has deployed a massive server farm. So far the valuation and servers having borne fruit, however, Elon Musk recently announced that Grok-3 is in its final stages of training and that “Grok-3 is scary smart and outperforms any released model we're aware of"

Leadership and Key Team Members

Spearheaded by Elon Musk and AI scientists like Yuhuai “Tony” Wu, xAI has the potential to be a leader in the AI/LLM race. 

Top Models

Grok-3 (upcoming), Grok-2, Grok 

Pros

• Deep integration with Twitter/x.com and access to tons of user content
• The general ethos around not censoring content
• Access to vast amounts of capital and resources thanks to Elon Musk

Cons

• Early performance was not in line with leading competitor offerings 
• Limited public details on long-term development plans

What to Watch

The launch of Grok-3 will likely be a pivotal moment for xAI and their ability to compete with leading LLM research labs like OpenAI and Anthropic. 

8. Mistral - LeChat

Overview

Mistral’s LeChat represents the cutting edge of open-source AI, combining efficient performance with a highly adaptable framework. Designed to deliver state-of-the-art results while maintaining flexibility, LeChat is a testament to Mistral’s commitment to innovation and accessibility in the AI space. Its lightweight architecture and open-source nature make it a standout choice for developers and researchers seeking powerful yet resource-efficient AI solutions.

Leadership and Key Team Members

Mistral is led by a dynamic team of ex-academics and startup entrepreneurs, bringing together deep technical expertise and a strong entrepreneurial spirit. This combination positions Mistral for rapid growth and continuous innovation. The team’s focus on open-source development and community-driven progress ensures that Mistral remains at the forefront of AI advancements.

Top Models

Mistral has developed several high-performing models, including:

• Mistral Large: A flagship model designed for high-performance tasks, offering robust capabilities for complex AI applications.
• Pixtral Large: A versatile model optimized for multimodal tasks, combining text and image processing.
• Mistral 3B/8B: Lightweight yet powerful models tailored for efficiency, making them ideal for deployment on modest hardware.

Pros

• Agile and Transparent Development: Mistral’s open-source approach fosters transparency and rapid iteration, enabling the community to contribute to and benefit from ongoing improvements.
• Efficient Performance: LeChat’s models are optimized to deliver high performance even on resource-constrained hardware, making them accessible to a wider range of users.
• Strong Community Support: A vibrant and growing community drives innovation, ensuring that Mistral’s models remain at the cutting edge of AI technology.
• Adaptability: The framework’s flexibility allows for easy customization and integration into diverse applications, from research to enterprise solutions.

Cons

• Niche Market Focus: Mistral’s emphasis on open-source and lightweight models may limit its appeal to larger enterprises with high-volume, resource-intensive needs.
• Scaling Challenges: While efficient, the models may face challenges when scaling to meet the demands of high-volume enterprise use cases, particularly in industries requiring heavy computational resources.
• Competition: The AI landscape is highly competitive, with well-established players offering proprietary solutions that may overshadow Mistral’s open-source offerings and Meta’s Llama offering may get more open source developer engagement 

What to Watch

With Mistral being Europe’s primary AI offering, expect significant domestic support for the firm as they race to compete with the US and China to offer leading AI solutions. 

9. Cohere

Overview

Cohere specializes in serving private and secure AI models for enterprises, they brand themselves as the “The all-in-one platform for private and secure AI” 

Leadership and Key Team Members

A dedicated team of AI researchers and business veterans drives Cohere’s vision for scalable NLP solutions.

Top Models

Command-r7b-12-2024, command-r-plus-08-2024, Command series 

Pros

• Niche focus 
• Strong leadership, including executives that were early AI innovators
• Retrival model focus could be competitive advantage

Cons

• Small firm, competing in highly competitive enterprise sectors
• Limited public awareness and limited consumer-facing applications 

What to Watch

Expect a push for increased enterprise adoption and new model iterations that further enhance text processing. They are attempting to focus on adding AI functionality to complex industries like Financial Services, Healthcare, Manufacturing, and Energy. 

10. Perplexity

Overview

Perplexity AI offers a unique fusion of search and conversational capabilities, delivering nuanced responses with near real-time citations and comprehensive information retrieval. In the purest sense, Perplexity is not a deep research LLM lab generating frontier models, and perhaps that may change, but we’re adding them to this spot given that they’re using open source models and their live search index in an innovative way and challenging incumbents in search like Google to rethink their models and that’s what innovation is all about. 

Leadership and Key Team Members

Helmed by a nimble team of tech entrepreneurs, Perplexity bridges the gap between traditional search and modern AI chatbots.

Top Models

Sonar Models, Deep Research Agent

Pros

• Innovative blend of search and chat functionalities
• Quick adaptation to emerging trends, like the recent launch of Deep Research in response to OpenAI’s offering 
• User-friendly interface with intuitive design

Cons

• Smaller market presence relative to industry giants
• Unclear if they will invest heavily in proprietary model development
• The existing subscription model may limit public adoption 

Honorable Mentions 

Microsoft – Phi-4

Overview & What to Watch:

Microsoft’s Phi-4 models are a family of powerful, cost-effective small language models with ultra-low latency engineered for enterprise needs—demonstrating that highly targeted solutions can be extremely profitable even when addressing niche problems, though success in these specialized applications does not guarantee broader market dominance.

Top Models:

Phi-4, Phi-3

Amazon – Nova

Overview & What to Watch:

Amazon’s Nova series, available exclusively on Amazon Bedrock, delivers frontier intelligence with exceptional price performance. It remains to be seen whether Amazon or Microsoft will attempt to enter the super-intelligent frontier model race currently led by OpenAI, DeepSeek, Anthropic and Google. 

Top Models:

Nova Micro, Nova Lite, Nova Pro, Amazon Nova Premier (Coming Soon)

Baidu

Overview & What to Watch:

Baidu leverages its vast data resources to build conversational AI with a strong emphasis on natural language processing and voice recognition for the Chinese market, showing that specialized performance in a regional context can be highly profitable even if international reach remains limited; strategic expansion and enhanced multilingual support could allow multiple players to succeed across segments.

Top Models:

Ernie 

Nvidia – Nemotron Series

Overview & What to Watch:

Nvidia’s Nemotron series, built on the robust NeMo framework using advanced pruning, distillation, and alignment techniques, powers agentic AI applications across diverse deployments; its success in niche enterprise solutions underscores that even specialized models can be lucrative, while broadening multilingual and multimodal capabilities could foster multiple winners across segments. This agentic focus could make Nvidia’s offering interesting to developers and power users. 

Top Models:

Nemotron-4-340B-Instruct, Nemotron-4-Mini-Hindi-4B, Nemotron-3-8B-Base-4k

Tencent

Overview & What to Watch:

Tencent’s AI initiatives focus on integrating chatbots within gaming and social platforms to create unique content like 3D assets for games. 

Top Models:

Tencent Hunyuan3D-2 

ByteDance

Overview & What to Watch:

ByteDance leverages its massive user base and content ecosystem to experiment with AI to generate content, for example, they recently launched an AI model that went viral for its “deepfake capabilities that animate photos” 

Top Models:

OmniHuman-1 multimodal model

Kimi (k1.5)

Overview & What to Watch:

Kimi by MoonshotAI is a promising open-source model with an innovative architecture currently in early development, showing potential for niche success through its agile, community-driven approach. Early testing show it is competitive or bests OpenAI’s top models in some contexts: 

Top Models:

Kimi k1.5

Yi by 01.ai

Overview & What to Watch:

Yi is a compact, efficient chatbot focused on streamlined, lightweight performance that offers high accessibility for early deployments.

Top Models:

Reka

Overview & What to Watch:

Reka AI is a company specializing in developing cutting-edge multimodal artificial intelligence models, allowing users to interact with and understand information across various formats like text, images, and videos; their key focus is building generative AI models that can perform complex tasks like generating text based on images, understanding video content, and providing insightful analysis across different media types, with their primary product being a multimodal assistant called "Yasa" that can be customized for different enterprise applications.

Top Models:

Reka Spark (2B parameters): Compact, fully multimodal, multilingual (32 languages), 128K context length; ideal for smartphones, robots, wearables, and home appliances.

Reka Edge (7B parameters): Mid-range, fully multimodal, multilingual, 128K context length; best for laptops, desktops, and high-end tablets.

Reka Flash (21B parameters): High-performance, fully multimodal, multilingual, 128K context length; suited for on-premises or private cloud deployment.

Reka Core (67B parameters): Most advanced, fully multimodal, multilingual, 128K context length; designed for complex use cases and model distillation.

LG AI Research

Overview & What to Watch:

LG AI Research is a think tank that develops AI technology to improve customer experiences and solve global challenges. LG AI Research's mission is to advance AI for a better life.

Top Models:

EXAONE

Predictions for 2025

• Open Source Momentum: Open source will likely grow in reach—with DeepSeek providing significant momentum as community-driven innovation accelerates. This can create a virtuous flywheel for the entire industry where the open sharing of breakthroughs lifts open and closed source research firms alike. 
• Google’s Rising Influence: Don’t count out Google; its new models are fast, intelligent, competitive, and seamlessly integrated with an expansive tech ecosystem. Google’s ability to distribute to a large user base and its search monopoly gives it powerful levers to pull. It fumbled early in the AI race, but we don’t expect that to continue–they have too much to lose. 
• Mag7 CapEx: We expect further advancements not just in software but hardware as well. Specifically we expect well-capitalized goliaths like Amazon and Microsoft to continue developing their own hardware and infrastructure to support growing AI demand. It remains to be seen if Amazon and Microsoft enter the frontier model race, but at a minimum, you can expect the development of enterprise-focused hardware to drive down costs and increase their margins, making inference and training less costly in the process. 
• Meaningful Profitability from AI: A big attack on AI has been the scale of capital investment with relatively little payback. 2025 could bring stories of significant revenue growth via increased efficiency. What that does to jobs, remains to be seen. 
• Anthropic and xAI Push for Top Spots: Anthropic is expected to drop a breakthrough, a large-scale model that challenges OpenAI’s best reasoning models, and Grok-3 is rumored to be extremely competitive too. 
• First Single-Person Unicorn Company: On the back of the AI wave, startup Cursor grew to $100m ARR in 12 months, with a team of just 20 and no marketing. With the advancement in agentic AI, we wouldn’t be surprised to hear rumblings of single or 5-person teams reaching similar growth trajectories. (This is crazy sounding, we know). 

Important note about consumer apps vs. enterprise LLM adoption 

While artificial intelligence apps are not the same as large language models (LLMs), for simplicity we’re grouping them here so a broad audience can appreciate the current state of AI innovation. Even when addressing niche problems, enterprise solutions can generate significant profits because businesses are willing to pay a premium for efficiency and reliability. In contrast, consumer models need to be versatile enough to serve a broad audience. Success in one market segment doesn’t automatically guarantee overall dominance—there’s plenty of AI “pie” for multiple labs to thrive by tailoring their innovations to the specific needs of their customers.

It will be interesting to see how specialized AI (enterprise use cases) branches or exists with general intelligence LLMs which are part of the race to ASI/AGI. We see a world where both add value, however, the super-intelligent model race seems to be a focus of the public and media. 

To close, in the interest of not making this a 100,000-word article, we suggest that a company like Cohere could be successful in tackling enterprise needs while still not delivering an exceptional consumer product with high intelligence on a range of tasks. Overall, the goal of this article is to give the reader a good snapshot of the current state of AI innovation and leadership. We acknowledge that there are some limitations to our methodology and approach. 

Conclusion

In summary, on an aggregate basis, OpenAI, Google, and Anthropic offer the best LLMs today. 

We don’t expect these positions to be static, but for various reasons, we expect these leaders to remain among the top LLM providers going forward. 

As we reflect on the state of AI development in late 2024 (DeepSeek) and evaluate progress in Q1 2025, the pace of innovation is accelerating. The energy around open source facilitates knowledge sharing and will likely further that acceleration. 

Seeing breakthroughs emerging from established tech giants and nimble open-source initiatives has been exciting. We hope for a future of AI that offers a blend of performance, accessibility, and innovation that will shape our digital lives for years to come.

Disclosure: 

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