ARTICLE: AI Chatbot Detailed Comparison: ChatGPT vs. Claude vs. Kimi vs. Copilot vs. Google AI vs. DeepSeek vs. Grok

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AI tools have knowledge cutoff which refers to the specific date at which an AI model's training data ends, meaning it does not have access to any information or events that occurred after that date; essentially, it represents the limit of the AI's knowledge based on the data it was trained on.

"what is your knowledge cutoff?"

ChatGPT => My knowledge cutoff is October 2023. However, I can fetch up-to-date information from the web if needed. Let me know if you need the latest details on Primavera or any other topic!

Claude.ai => My knowledge was last updated in April 2024. When I discuss events after that date, I respond as a well-informed person from April 2024 would if they were speaking to someone in January 2025. I aim to be transparent about this limitation while still engaging meaningfully in discussions about more recent events based on how you present them to me.

Google AI Studio => My knowledge cutoff is September 2021. This means I don't have access to information or events that occurred after that date.

DeepSeek r1 32b installed locally  => My knowledge is current up to July 2024. I'll do my best to provide accurate and comprehensive information for you

Copilot => I don't have a specific knowledge cutoff date. My knowledge is constantly being updated, and I can always search for up-to-date information. If you have any specific questions or need the latest information on a topic, feel free to ask!

Kimi => My knowledge cutoff is October 2023.

"draw a hierarchical diagram of project management system"

ChatGPT => got it wrong and in text mode 👎

Claude.ai => the best answer with a Mermaid graph TD (top-down) diagram! 👍

Google AI Studio => good and fast in text mode!

DeepSeek => good in text mode.

Copilot => good in text mode.

Kimi => the best answer in text mode (Kimi doesn't even need a login 😀)

"generate code using <my language and tool>"

ChatGPT => good.

Claude.ai => the best result!

Google AI Studio => good and fast!

Copilot => partially failed and it got stuck instructing me to do something inside <my tool> but that feature does not exist. I pointed it out and it said, "Oh I see, try this one instead..." and it gives the same wrong response again and again! Why does it boast about its knowledge cutoff as current saying, "I don't have a specific knowledge cutoff date. My knowledge is constantly being updated, and I can always search for up-to-date information"? That is BS if you ask me.

DeepSeek V3 (chat.deepseek.com) => good.

Kimi => the best result!

"generate this code..."

ChatGPT => good.

Claude.ai => the best result!

Google AI Studio => good and fast!

Copilot => good.

Kimi => the best result!

DeepSeek r1 32b installed locally => is slow and the fan revs up on my MacBook Pro M2 Max 16.2" with 64GB RAM and the code it generated is incomplete.

DeepSeek r1 14b installed locally => is fast but the code is much more incomplete.

DeepSeek r1 7b installed locally => is faster but it generated code using a completely different programming language and repeated the same even after I pointed it out! r1 7b is unreliable despite its recent knowledge cutoff.

Comparisons

What are these tools called?

1. ChatGPT, Claude, and Kimi:

• General Term: These are all broadly categorized as Large Language Models (LLMs) or Conversational AI tools.

• Specific Term:

  • ChatGPT: Developed by OpenAI, it is specifically a Generative Pre-trained Transformer (GPT) model.

  • Claude: Developed by Anthropic, it's often described as an AI assistant or conversational AI.

  • Kimi: This also falls under the category of Large Language Models, with a focus on speed and ease of use.

• Common Features:

  • They excel at natural language processing (NLP).

  • They have a conversational interface where users interact through text prompts.

  • They can generate text, code, and other forms of content based on training data.

2. GitHub Copilot:

• General Term: It's considered an AI Pair Programmer or an AI-powered Code Completion Tool.

• Specific Term: It's often described as an AI-powered code assistant. It's built on top of OpenAI's Codex model, which is a variant of the GPT models specifically trained on code.

• Common Features:

  • It integrates directly into code editors.

  • It provides real-time, in-line code suggestions and auto-completions.

  • It learns from your coding patterns and provides context-aware suggestions.

3. Google AI Studio (formerly MakerSuite):

• General Term: It's considered a Generative AI Prototyping Platform or a Platform for AI Model Exploration.

• Specific Term: It's a tool from Google that allows users to experiment with Google's generative AI models, especially the PaLM API and Gemini API.

• Common Features:

  • It provides a web-based interface for interacting with AI models.

  • It's used for exploring and testing AI capabilities for various tasks, including those related to code.

  • It allows prompt engineering and experimentation with different AI models.

4. DeepSeek:

• General Term: DeepSeek is also an Large Language Model with an emphasis on Code Generation and understanding.

• Specific Term: Often described as an AI for Code focused on correctness, efficiency, and code documentation/refactoring capabilities.

• Common Features:

  • It generates code in multiple programming languages.

  • It focuses on the quality, efficiency, and maintainability of the generated code.

  • It prioritizes code correctness and adherence to coding standards and best practices.

  • It may be available with a conversational interface or be exposed as an API.
     

Here's a quick table summarizing the terms:

Tool	General Category	Specific Term	Key Feature
ChatGPT	Large Language Model (LLM), Conversational AI	Generative Pre-trained Transformer (GPT) model	Text-based AI, conversation, broad text generation
Claude	Large Language Model (LLM), Conversational AI	AI Assistant, Conversational AI	Detailed text output, complex reasoning
Kimi	Large Language Model (LLM)	Large Language Model (LLM)	Fast, Simple Text Output
GitHub Copilot	AI Pair Programmer, Code Completion Tool	AI-powered code assistant, AI code completion tool	Real-time, in-editor, code suggestions and completion
Google AI Studio	AI Prototyping Platform	Platform for exploring PaLM and Gemini APIs	Web-based, experimentation with AI models, prompt engineering
DeepSeek	Large Language Model, Code-focused AI	AI for Code, Code generation LLM	Focus on code quality, efficiency, refactoring and understanding

Why These Terms Matter:

• Understanding Capabilities: Knowing the category of a tool helps you understand its strengths and weaknesses. For instance, an LLM like ChatGPT is good for language-based tasks, while an AI pair programmer like Copilot is better for real-time code assistance.

• Choosing the Right Tool: Using the correct terminology helps you choose the most appropriate tool for your specific need.

• Navigating the AI Landscape: The AI field is constantly evolving. Knowing these terms helps you stay informed and understand the latest developments.

• Effective Communication: Using the correct terms allows for clearer communication about these tools when collaborating with others.
   

Here is what Gemini says about ChatGPT vs Claude.ai (ChatGPT has the "first to the market" advantage with more integrations)

"ChatGPT vs Claude.ai for coding"

When comparing Claude AI and ChatGPT for coding, Claude generally performs better for generating accurate and optimized code, particularly in complex scenarios, while ChatGPT might be more versatile with a wider range of features and integrations, making it a good choice for basic code generation and learning new concepts; however, the best choice depends on your specific coding needs and priorities regarding code quality and complexity.
 

Key points to consider:

 

• Context awareness: Claude is often praised for its ability to maintain context within a codebase, leading to more consistent and relevant code suggestions.
   

• Complexity handling: For complex coding challenges, Claude's reasoning capabilities can provide superior solutions compared to ChatGPT.
   

• Versatility: ChatGPT may be more versatile with additional features like generating different code styles, explaining concepts, and offering broader language support.
   

• Integrations: ChatGPT might have a wider range of integrations with existing developer tools and platforms.
   

• Code accuracy: Many users report that Claude produces cleaner and more error-free code compared to ChatGPT, especially when dealing with intricate coding tasks requiring deep understanding of the problem domain.

• Code Quality:

• Claude tends to produce more optimized and error-free code with better context awareness, making it better for intricate projects.
• ChatGPT may sometimes generate code with potential issues that require further refinement.
   

• Explanation and Reasoning:

• Claude often provides detailed explanations and reasoning behind its code generation, helping developers understand the logic and decision-making process better.
• ChatGPT might offer more concise explanations.
   

• User Interface and Interaction:

• Some users find Claude's interface more intuitive for coding tasks, allowing for a smoother workflow with better prompts and feedback loops.
   

• Speed:

• ChatGPT might be faster for generating basic code snippets quickly.
• Claude may take slightly longer to produce more complex and well-structured code. 

 

When to use ChatGPT for coding:

• General-Purpose Code Generation
• Explaining and Understanding Code
• Troubleshooting and Debugging
• Code Translation and Conversion
• Learning and Exploration
• Creative Coding and Rapid Prototyping
• Need a quick code snippet for a simple task
• Want a conversational style for brainstorming ideas

 

When to use Claude for coding:

• Working on complex coding projects requiring detailed reasoning and accurate code generation
• Complex Reasoning and Logic Problems
• Longer Code and Contextual Understanding
• Natural Language Understanding and Instruction Following
• Want in-depth explanations for code logic and best practices
• Code Documentation and Explanation
• Creative Problem Solving and Code Generation
• Need to ensure code quality and maintainability

When to use Kimi for coding:

• Idea Generation and Brainstorming
• Code Generation and Writing
• Code Explanation and Understanding
• Debugging and Troubleshooting
• Documentation and Code Comments
• Refactoring and Optimization

When to use Google AI Studio for coding:

• Prototyping AI-Powered Features
• Prompt Engineering and Model Understanding
• Data Preparation and Transformation for AI Models
• AI Model Integration Experiments
• Educational Purposes

When to use Copilot for coding:

• Real-Time Code Completion and Suggestions
• Rapid Prototyping and Experimentation
• Boilerplate Code Generation
• Exploring New Libraries and APIs
• Code Documentation and Comments
• Code Refactoring and Optimization (Limited)

Key Characteristics of GitHub Copilot:

• Real-Time Integration: Works directly within your code editor, providing suggestions as you type.

• Context-Aware: Understands the context of your code, language, and project.

• Predictive: Anticipates your needs and generates code based on your patterns.

• Productivity Booster: Significantly speeds up the coding process by automating repetitive tasks.

• AI Pair Programmer: Acts as a helpful assistant that you can collaborate with while you code.

When to use DeepSeek for coding:

• Code Generation with a Focus on Correctness and Efficiency
• Code Explanation and Understanding with Detailed Insights
• Refactoring and Code Improvement with a Focus on Best Practices
• Multi-Language Code Support with a Focus on Specific Syntax
• Integration with Development Workflows

How ChatGPT, Claude, Kimi, Copilot, Google AI Studio and DeepSeek differ from each other

1. Core Approach and Interface:

• ChatGPT, Claude, Kimi (Conversational AI):

  • Interface: Primarily text-based, conversational interfaces. You interact through prompts and questions.

  • Approach: They excel at understanding natural language and providing text-based responses, including code snippets, explanations, and suggestions.

  • Focus: General-purpose AI that can handle a broad range of coding tasks, but often require more explicit instructions.

• GitHub Copilot (AI Pair Programmer):

  • Interface: Directly integrates into code editors like VS Code, Visual Studio, and others.

  • Approach: Provides real-time, in-line code suggestions and auto-completions as you type.

  • Focus: Focused on code generation within your coding environment and accelerating the coding process with its predictive capabilities.

• Google AI Studio (AI Prototyping):

  • Interface: A web-based environment for experimenting with AI models.

  • Approach: Designed for exploring and testing AI capabilities, particularly Google's PaLM and Gemini models, and how they can be used in coding-related tasks.

  • Focus: Prototyping AI-powered features rather than providing direct code assistance.

• DeepSeek (Code-Focused AI):

  • Interface: It may integrate with code editors or provide an API for use.

  • Approach: Emphasizes generating high-quality, efficient, and well-documented code, along with strong refactoring capabilities.

  • Focus: Designed for code understanding and generation with a strong emphasis on correctness and adherence to best practices.
     

2. Strengths and Weaknesses for Coding:

Feature	ChatGPT	Claude	Kimi	GitHub Copilot	Google AI Studio	DeepSeek
Code Generation	Good for quick snippets, basic functions	Strong for complex logic, longer blocks	Good for boilerplate, rapid prototyping	Excellent in-line, real-time suggestions	For exploring AI-powered code generation	High quality, efficient functional code
Explanation	Good, but sometimes lacks detail	Very detailed, comprehensive explanations	Good for basic explanations	Limited; focuses on suggestions	For exploring AI explanations	In-depth, with focus on logic
Debugging	Good for identifying general errors	Capable of identifying more complex issues	Helpful for simple troubleshooting	Limited debugging capabilities	Useful for exploring AI-based debug	Strong in highlighting code issues
Refactoring	Limited, basic suggestions	Limited but can suggest some improvements	Limited refactoring suggestions	Basic suggestions	Limited refactoring exploration	Strong in code refactoring
Complexity Handling	Struggles with complex domain logic	Stronger with complex domain logic	May struggle with complex problems	Limited, but context-aware	Designed to test AI complex reasoning	Strong in understanding intricate logic
Context	Limited by conversational history	Good context handling for longer conversations	Moderate context, quick responses	Excellent within the current file	Prototyping AI to understand context	Designed to understand project context
Speed	Generally fast responses	Generally fast responses	Fast responses, great for quick tasks	Instant feedback as you type	Varies depending on the models	High performance and efficient code
Real-Time Coding	Not designed for real-time coding	Not designed for real-time coding	Not designed for real-time coding	Excellent real-time integration	Not a real-time coding tool	May integrate with real-time workflows
Integration	Uses a conversational interface	Uses a conversational interface	Uses a conversational interface	Direct integration with code editors	Web-based for AI experimentation	API or IDE Integration
Security Awareness	Basic security guidance	Improved security awareness	Limited security awareness	No inherent security checks	Useful for exploring AI for code security	High security focus
Learning Curve	Easy to start using	Easy to start using	Very easy to use	Takes some time to get used to	Specific usage requires some learning	Designed for developer ease of use

3. Ideal Use Cases:

• ChatGPT, Claude, Kimi:

  • Learning: Grasping fundamental concepts, exploring new libraries, understanding code snippets.

  • Brainstorming: Generating ideas, exploring multiple approaches, writing initial drafts.

  • Quick Fixes: Obtaining simple code snippets, explaining errors, generating basic functions.

  • Code Documentation: Creating simple comments and documentation based on code.

• GitHub Copilot:

  • Rapid Development: Accelerating the coding process through code completion and in-line suggestions.

  • Boilerplate Code: Generating standard project setups and repetitive code blocks.

  • API and Library Exploration: Learning how to use new libraries and APIs through code examples.

  • Enhancing Productivity: Optimizing the coding workflow with real-time assistance.

• Google AI Studio:

  • Prototyping AI Features: Testing and experimenting with AI models for code-related tasks.

  • Prompt Engineering: Developing effective prompts for code generation.

  • AI Model Exploration: Learning about the capabilities and limitations of different AI models.

  • Data Preparation for AI: Preparing data and examples for AI models.

• DeepSeek:

  • High-Quality Code: Generating code that is both correct and efficient.

  • Refactoring and Code Improvement: Improving code readability and maintainability.

  • Understanding Complex Code: Analyzing and understanding intricate code bases.

  • Multi-Language Development: Working across different programming languages.
     

4. Choosing the Right Tool:

• For General Coding Assistance, Explanation, and Idea Generation: ChatGPT, Claude, or Kimi can be effective depending on complexity and the required level of detail. Claude is often preferred for more in-depth explanations and complex logical reasoning, while ChatGPT is a versatile, widely accessible option, and Kimi is often the fastest and easiest to use for simple tasks.

• For Real-Time Code Completion and Productivity: GitHub Copilot is your best choice.

• For Experimenting with AI Models and Prototyping Features: Google AI Studio is the most appropriate.

• For High-Quality Code Generation, Refactoring, and Code Understanding with a focus on Best Practices: DeepSeek is likely to be the most suitable option.
   

Key takeaway:

Each of these tools plays a unique role in the coding landscape. Understanding their individual strengths and limitations allows you to leverage them effectively based on your specific needs and coding workflow. They can also be used in combination - using ChatGPT or Claude to gain a deep understanding of a coding problem, then using Copilot or DeepSeek to write the solution, or Google AI Studio to experiment with various approaches.

Conclusion

This article is a work-in-progress and will be updated frequently.

For code generation, even though DeepSeek and Copilot claim to have a "more recent knowledge cutoff" than Claude.ai, they are not better or even as good as Claude.ai or Kimi.ai. That way, Google AI Studio or Kimi with much older cutoff dates are better and faster than DeepSeek and Copilot.

Ranking

1. Claude.ai - the BEST
2. Kimi.ai - second best - generates response from the web and can also display web results in the sidebar
3. ChatGPT or Google AI Studio or Copilot

Claude.ai from Anthropic is the BEST for code generation than any other AI tool (it generates beautiful and complete code) followed by Kimi.ai, Google AI Studio and ChatGPT. Google AI Studio is faster.

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[TELUGU]

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Not sure why they could not choose a proper name in the first place.

Android app developer Dylan Roussel has apparently leaked a company change-log that says “Bard is now Gemini” which is the new model to compete with OpenAI’s GPT-4.

“Bard is now Gemini. Gemini is the best way to get direct access to Google Al. All the collaborative capabilities you know and love are still here, and will keep getting better in the Gemini era,” reads the change-log. However, the company’s however, did not make an official comment on changing Bard’s name to Gemini.

“We’ve also evolved the Ul to reduce visual distractions, improve legibility, and simplify the navigation,” according to the document. The log said that Google will debut voice chat with Gemini, as well as a new “Ultra 1.0” model with “Gemini Advanced,” a paid plan that offers ChatGPT Plus-like file uploading features.

“Gemini Advanced gives you access to our most capable Al model, Ultra 1.0. With our Ultra 1.0 model, Gemini Advanced is far more capable at highly complex tasks like coding, logical reasoning, following nuanced instructions, and creative collaboration,” read the Google document.

Gemini Advanced will continue to expand with new and exclusive features in the coming months, including expanded multi-modal capabilities, even better coding features, as well as the ability to upload and more deeply analyze files, documents, data, and more. Gemini Advanced is a paid plan available in over 150 countries and territories. The Gemini app is coming soon, starting with English.

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