A Comparison of the Top AI Models: Features, Use Cases and Cost

Once the stuff of science fiction, artificial intelligence is now a mainstream technology. What started with the 2022 release of OpenAI’s GPT-3.5 language model and ChatGPT has evolved into a full-blown arms race to build smarter and smarter AI models. The release of DeepSeek-R1 has only intensified the momentum, driving companies to develop systems with more advanced reasoning capabilities at a lower cost.

But not all AI models are created equal, and the industry metrics used to compare them can be difficult for everyday users to understand. The list below highlights some of the top AI models available today, breaking down their defining features and strengths so you can determine the one that best fits your specific needs.

What Is an AI Model?

An AI model is a type of computer program trained on large datasets to recognize patterns, make predictions and generate outputs with minimal human intervention. The process begins with human researchers feeding the model relevant data that has been cleaned and prepared ahead of time. Then, they apply algorithms — sets of mathematical rules and instructions — that help the model learn how to identify specific patterns within the training data. Once an AI model has been tested for accuracy and properly trained, it should be able to generalize what it has learned and analyze new, unseen data on its own.

AI models are designed to perform specific tasks, with more advanced models handling more complex problems. Depending on how they’ve been trained, AI models can do anything from recognizing faces in video footage to translating text into other languages.

More on AI ModelsWhat Are Foundation Models?

Top AI Models: A Comparison

The following list includes AI models developed by tech giants and independent researchers alike, along with some key metrics to help you compare them at a glance.   

GPT-4o

GPT-4o is a model created by OpenAI, the company behind ChatGPT. The model is inherently multimodal, processing and producing text, images, audio and video. With a response time of 232 milliseconds, it also makes conversations feel more natural, offering translation in more than 50 languages.   

• Capabilities: Processes text, image, audio and video data; responds to audio inputs in 232 milliseconds. 
• Use cases: Translating languages; generating images; summarizing and generating text; completing coding problems.  
• Benchmarks: Stands out in math, coding, language translation and complex reasoning. 
• Availability: Users with a free ChatGPT plan can gain limited access to GPT-4o, with greater access using a Plus, Team or Pro plan. 
• Cost: Fine-tuning pricing starts at $3.75 per 1 million input tokens and $15 per 1 million output tokens.  

OpenAI o1

OpenAI o1 followed the release of GPT-4o, blowing away GPT-4o in competition math, competition code and PhD-level science questions. Trained through reinforcement learning, o1 can develop chains of thought to produce more thoughtful responses, solve complex problems step by step and learn from its mistakes.  

• Capabilities: Demonstrates advanced reasoning; improves its performance by learning from past mistakes; delivers more thoughtful responses.  
• Use cases: Writing and debugging code; solving complicated math problems in quantum computing; analyzing cell data in healthcare. 
• Benchmarks: Rivals human experts in reasoning-based topics, excelling in college mathematics, professional law and physics. 
• Availability: Users with a ChatGPT Team account can access OpenAI o1, while Pro and Enterprise users can access OpenAI o1 pro mode.  
• Cost: Pricing starts at $15 per 1 million input tokens and $60 per 1 million output tokens. 

OpenAI o3-mini

Labeled by OpenAI as the “most cost-efficient model” in the o model series, OpenAI o3-mini comes with popular developer features like developer messages, function calling and structured outputs. It also offers low, medium and high reasoning effort settings, so users can tailor the model to both basic and more challenging problems. 

• Capabilities: Prioritizes problem-solving or speed in different situations; focuses on STEM-related problems; assesses prompts to develop safer responses.
• Use cases: Conducting STEM research; solving complex coding problems; analyzing and answering questions about images. 
• Benchmarks: Performs well in STEM topics, especially math, science and coding.  
• Availability: Users with a ChatGPT Team account or those using the API on tiers 1-5 can access OpenAI o3-mini. 
• Cost: Pricing is $1.10 per 1 million input tokens and $4.40 per 1 million output tokens. 

Claude 3.7 Sonnet

Claude 3.7 Sonnet is one of the latest large language models released by Anthropic, an AI research and development company that counts Google and Amazon among its investors. Claude 3.7 Sonnet features a standard and extended thinking mode, with the latter giving it the ability to reflect before responding. This allows it to handle difficult topics like coding. 

• Capabilities: Pivots between standard and extended thinking modes; caters to real-world coding tasks; develops detailed agentic workflows. 
• Use cases: Writing code; automating computer use; gleaning insights from data visualizations; building chatbots; supporting robotic process automation.
• Benchmarks: Stands out in coding, software engineering problems and agentic tool use.
• Availability: Claude 3.7 Sonnet is available on the Anthropic API, Amazon Bedrock and Google Cloud’s Vertex AI. All Claude.ai users can also access a basic chat experience with Claude 3.7 Sonnet.  
• Cost: Pricing starts at $3 per 1 million input tokens and $15 per 1 million output tokens. 

Gemini 2.5 Pro 

Google has added to its family of Gemini models with the release of Gemini 2.5 Pro. This multimodal model can handle large data sets with a context window of 1 million tokens, create code for web development applications and solve problems that require advanced reasoning. And Gemini 2.5 Pro Preview offers even more coding options for developers. 

• Capabilities: Processes large volumes of data; caters to web development coding needs; possesses the reasoning needed to handle difficult coding problems.  
• Use cases: Developing code; designing interactive animations; building games; producing data visualizations. 
• Benchmarks: Demonstrates high-level reasoning for subjects like physics, mathematics and coding. 
• Availability: Gemini 2.5 Pro is available in the Gemini API, Google Studio and the Gemini App. Enterprise customers can access it via Vertex AI. 
• Cost: Pricing is $2.50 per 1 million input tokens and $15 per 1 million output tokens. 

DeepSeek-R1

Developed by Chinese AI startup DeepSeek, DeepSeek-R1 is an open-source AI model that took the industry by storm, proving that a more compact and cost-efficient model can compete with those made by tech giants. Trained through reinforcement learning, DeepSeek-R1 showcases extensive context and chain-of-thought reasoning to tackle complex subjects and situations.  

• Capabilities: Explains complex math and scientific concepts; improves its performance on its own over time; evaluates text and data to provide relevant insights. 
• Use cases: Writing and debugging code; solving difficult math problems; producing creative written content; running customer service chatbots.
• Benchmarks: Excels in mathematics, coding and general reasoning. 
• Availability: DeepSeek-R1 is open-source and available under the MIT License. It can be found on deepseek-r1.com and other platforms like Microsoft Azure, Amazon Web Services and Hugging Face. It also powers DeepSeek’s eponymous chatbot.    
• Cost: Pricing is $0.14 per 1 million input tokens and $2.19 per 1 million output tokens. 

Grok 4

Developed by Elon Musk’s AI company xAI, Grok 4 shares the same name as the Grok chatbot it powers. The model builds upon the foundations of its predecessor, Grok 3, offering stronger reasoning skills, native tool use and support for text, image and voice inputs. Grok 4 was trained with reinforcement learning, so it can evaluate its process, fix its mistakes and adjust its performance over time. It also comes in a more powerful “heavy” version, which has a team of AI agents that work together as a sort of “study group,” according to Musk, collaborating to solve complex tasks.

• Capabilities: Autonomously browses the web, X and other news sources for up-to-date information; breaks down problems into manageable steps; handles text, voice and image inputs; comes with a ‘Voice Mode’ that can converse back and forth with users. 
• Use cases: Researching current events; building apps that require long-context reasoning; solving advanced math and coding problems; holding natural voice conversations; analyzing visual data. 
• Benchmarks: Excels in math, coding, science, abstract reasoning and pattern recognition; achieves 50.7% on Humanity’s Last Exam (the first-ever model to do so).
• Availability: Available to Premium+ and SuperGrok subscribers on X and Grok; API access also available to developers; Grok 4 Heavy is only available to SuperGrok Heavy subscribers.
• Cost: Premium+ plans start at $30/month; SuperGrok plans start at $30/month and SuperGrok Heavy is $300/month.

Llama 4 Maverick

Part of Meta’s Llama 4 family, Llama 4 Maverick marks the company’s transition from the Llama 3 family. The model is natively multimodal and runs on 17 billion active parameters. However, Llama 4 models only need to activate a small number of parameters to operate, lowering their cost and latency.   

• Capabilities: Needs only a fraction of its parameters for efficiency; runs on a single Nvidia H100 DGX host; performs well in image and text understanding. 
• Use cases: Building multilingual chatbots; analyzing documents; producing videos and images for marketing campaigns.   
• Benchmarks: Surpasses competitor models in reasoning, coding, multilingual capabilities and long-context scenarios.  
• Availability: Llama 4 Maverick can be downloaded from the Llama website and Hugging Face. Users can also use Meta AI with Llama 4 through the Meta website, Instagram Direct, Messenger and WhatsApp. 
• Cost: Pricing is $0.19 per 1 million input tokens and $0.49 per 1 million output tokens. 

Mistral Medium 3

Mistral Medium 3 is intended to provide Mistral AI users with an affordable AI model that still performs at a high level. The latest addition to Mistral AI’s suite of commercial models, Mistral Medium 3 is designed to be multimodal, quick to deploy and easy to customize for different use cases. This makes the model ideal for enterprises looking to scale AI solutions.  

• Capabilities: Handles text and image inputs and outputs; does well with coding and STEM problems; adapts to various tasks with proper training. 
• Use cases: Writing and reviewing code; producing content in multiple languages; solving mathematical problems; analyzing images or visual content.
• Benchmarks: Exceeds comparative models like Llama Maverick 4 and GPT-4o in areas like coding, multilingual abilities and instruction following.  
• Availability: Mistral Medium 3 is available on Mistral AI’s La Plateforme and Amazon Sagemaker. It will also arrive on other platforms like Azure AI Foundry, IBM watsonx.ai and Google Cloud Vertex.  
• Cost: Free on La Plateforme with a Mistral AI account.

Aya Expanse 8B

Aya Expanse 8B is part of Cohere Lab’s Aya project, a global initiative that involves more than 3,000 independent researchers working to expand AI’s multilingual capabilities. Open-source and text-only, Aya Expanse 8B can produce outputs in 23 languages, including English, French, Chinese, Arabic, Korean and Vietnamese. 

• Capabilities: Specializes in text-based applications; produces outputs in 23 different human languages. 
• Use cases: Translating text into another language; producing content in multiple languages; summarizing written text.
• Benchmarks: Excels in multilingual performance and keeps up with comparable open-weight models like Llama 3.1. 
• Availability: Aya Expanse 8B can be accessed on Hugging Face or WhatsApp. 
• Cost: Aya Expanse 8B is free to use on WhatsApp or Hugging Face.

More AI CoverageWhat a Trump Administration Could Mean for AI Regulation

What Is the Best AI Model?

It’s impossible to designate an AI model as “the best” for various reasons. For one, the benchmarks used to compare these models are inherently broken and not very effective in general. Even when companies do manage to present helpful comparisons, the differences between models can be so slim that they’re inconsequential. 

And the AI race continues to provide improved AI technologies — the models of today are merely stepping stones for even more powerful systems on the horizon. So, when in doubt, just pick the AI model that most closely fits your particular needs, but keep an eye out for any upcoming models that could give you an even greater competitive advantage.

Frequently Asked Questions