ChatGPT took the world by storm with its ability to generate human-like text on demand. But when it comes to coding, ChatGPT still has some limitations. In this comprehensive guide, we‘ll explore the top 7 ChatGPT alternatives for powering up your coding in 2023.
Introduction to ChatGPT and Its Coding Capabilities
Launched in November 2022, ChatGPT is a conversational AI system created by Anthropic using self-supervised learning. It can understand natural language prompts and provide coherent responses as if a human wrote them.
Impressively, ChatGPT can also write, explain, debug, and even refactor code in multiple programming languages like Python, JavaScript, Go, Java, and more. It makes an excellent coding assistant by suggesting readable code variants, catching errors, filling in gaps, and clarifying concepts.
However, ChatGPT does have some drawbacks when applied specifically to coding:
- Accuracy issues – It sometimes generates wrong or inefficient code, especially for complex tasks
- Limited language support – Full capabilities only for Python, JavaScript, TypeScript, Ruby, Go
- Privacy concerns – Being a closed system, it captures all user interactions with no transparency
This is where specialized AI coding tools shine…
Why Consider ChatGPT Alternatives for Coding?
Dedicated code completion tools address ChatGPT‘s shortcomings by:
- Providing more accurate, secure and transparent experiences
- Specializing in coding with superior language support
- Enabling faster coding with real-time suggestions
- Catching subtle bugs and errors early
- Improving code efficiency and quality
Let‘s overview the top contenders:
Top 7 OpenAI Codex Alternatives for Coding
1. GitHub Copilot
As one of the most popular ChatGPT alternatives for coding, GitHub Copilot truly stands out with its context-aware suggestions tailored to your codebase.
Powered by OpenAI Codex and trained on billions of public GitHub repositories, Copilot generates shockingly intelligent code completions in line with your coding style and patterns.
The AI keeps improving the more you use Copilot, ensuring a highly personalized experience.
Key Features:
- Context-aware code suggestions
- Supports Python, JavaScript, TypeScript, Ruby and more
- Continuously learns from your code
- 60 day free trial, then $10/month
Use Cases: Rapid prototyping, catching errors early, writing boilerplate code
2. TabNine
TabNine touts itself as the fastest artificial coding assistant with sub-second response times. It‘s essentially autocomplete on steroids with advanced AI recommendations.
As you code, TabNine analyzes context and immediately suggests relevant code blocks tailored to your needs. The tool adapts to your coding style overtime.
Supporting over 20 languages, TabNine integrates seamlessly into IDEs like VS Code, Jetbrains and Vim. It‘s available as a free limited version or paid Pro subscription.
Key Features:
- Sub-second code suggestions
- Adaptive AI learns your style
- Broad language support
- Free version available
Use Cases: Maximizing coding speed, intelligent recommendations
3. Kite
Trusted by 100,000+ developers globally, Kite provides powerful coding productivity features enhanced by Copilot-grade AI.
It gives you real-time code completions, documentation, and error detection while you code. The tool indexes and cross-links everything in your codebase for intelligent recommendations.
Kite also stands out with its Python autocompletion. As you type, it suggests entire lines and function calls adapted to context.
Pricing starts at $20/month for individuals after a free trial.
Key Features:
- Code completions with Copilot-level AI
- Real-time documentation
- Indexes and cross-links codebase
- Specialized Python autocompletion
Use Cases: Increasing coding accuracy, surface documentation faster, navigating codebase quicker
4. Codota
Codota is an AI productivity tool specialized for Python developers who want blazing fast and contextualized code completions. It plugs directly into PyCharm, VSCode and Jupyter Notebook.
As you code in Python, Codota analyzes context and uses machine learning to predict the most likely completions for entire statements and blocks. This allows you to rapidly stitch together solid code.
Codota also highlights potential bugs and errors on the fly, explaining issues in plain English. It essentially serves as an inline Python coding assistant.
Pricing starts at $10/month for individuals.
Key Features:
- Rapid Python code completions
- Detects errors and quality issues
- Plain English explanations
- PyCharm, VS Code, Jupyter Notebook integration
Use Cases: Faster Python coding, catching bugs early, improving code quality
5. DeepMind‘s AlphaCode
On the cutting edge of AI coding assistants is DeepMind‘s AlphaCode system for code generation and reasoning. Their goal is to develop transparent and trustworthy AI that can master programming.
AlphaCode takes things to the next level by not only writing code, but also providing logical reasoning behind choices and explaining how the output achieves objectives. This ability to justify code builds additional trust.
Although not commercially available yet, AlphaCode gives us a glimpse into the promising future of AI coding tools. Some of its unprecedented capabilities include:
- Translating code between languages
- Improving efficiency of code
- Generating test cases
- Summarizing code functionality
As AI research continues at DeepMind and other labs, expect rapid advances in contextual coding assistants.
6. Anthropic‘s Claude
Founded by ex-OpenAI researchers, Anthropic created an AI assistant called Claude focused on safe, helpful and honest dialog.
Although not specialized for coding, Claude offers impressive language understanding and problem solving capabilities that can assist developers.
For example, Claude can translate explanations of code between programming languages, suggest ways to implement functionality more efficiently, provide debugging advice, generate tests, and more.
Claude asks clarifying questions if needed, while refusing inappropriate requests. It also avoids bias or deception by design.
Currently Claude is available via limited beta access packages priced up to $30/month for individuals.
Key Features:
- Advanced natural language understanding
- Code explanations and translations
- Refuses inappropriate requests
- Built to avoid deception
Use Cases: Getting unbiased coding advice, safe AI recommendations
7. Google Bard
Google introduced their own conversational AI called Bard to compete with chatbots like ChatGPT and Claude. Although still in an experimental phase, Bard aims to combine external world knowledge with the problem solving capabilities of deep learning models.
While not yet shown in action extensively for coding use cases, Bard does promise to offer conversational advice on prospective code in the future.
With the vast resources and talent Google possesses, we can expect rapid innovation of services like Bard for an ever-increasing range of applications. Coding and software development assistance could become a prime area for Google to challenge OpenAI and Anthropic.
It will be fascinating to observe how Google‘s offerings evolve compared to other enterprise-ready AI products from the likes of Anthropic, Cohere, You.com and more.
The next few years will witness astounding improvements in coding productivity thanks to advances in large language models and conversational AI.
Comparing the Top Alternatives
| ChatGPT Alternative | Key Features | Accuracy | Speed | Supported Languages | Explainability | Pricing |
|---|---|---|---|---|---|---|
| GitHub Copilot | Context-aware completions, learns from user | Very High | Medium | Python, JavaScript, TypeScript, Ruby | Low | $10+/month |
| TabNine | Ultra-fast response times, adaptive AI | High | Very Fast | Wide variety including Python, Java, C++ | Low | Free or $99+/year |
| Kite | Copilot-level completions, codebase indexing | Very High | Fast | Python, Java, Go, JavaScript, TypeScript | Medium | $20+/month |
| Codota | Rapid Python suggestions, error analysis | Very High | Very Fast | Python focused | High | $10+/month |
| DeepMind AlphaCode | Advanced code generation and reasoning | Very High | Fast | Multiple languages | Very High | Not yet available |
| Anthropic Claude | Safe and honest AI assistant | High | Medium | Natural language understanding | High | $30/month limited beta |
| Google Bard | Conversational advice on code | TBD | TBD | TBD | TBD | Experimental beta |
As shown in the comparison above, all the major alternatives excel in certain areas depending on your needs:
- GitHub Copilot stands out with personalization and language support
- TabNine is fastest for coding speed
- Kite offers Copilot-grade abilities plus docs/navigation
- Codota dominates for Python completion and analysis
- DeepMind AlphaCode is the most advanced and transparent
- Anthropic Claude prioritizes security and carefulness
- Google Bard promises versatile conversational applications
Make sure to factor in accuracy, speed, language needs, constraints around privacy or bias, and costs into your decision making process.
Optimally, I recommend combining a few complementary tools like a fast native extension with an advanced context-aware service.
Key Takeaways and Next Steps
The field of AI coding assistants is rapidly evolving with players like OpenAI, DeepMind, Anthropic and Google making astounding progress leveraging large language models.
Specialized coding tools now clearly outperform ChatGPT with superior speed, accuracy, language skills, and transparency for software development tasks.
When choosing alternatives, first decide which coding languages to target and what‘s most important – raw speed, personalization, transparency etc based on your workloads.
Then explore integrating a combination of tools, likely starting with Copilot or TabNine before checking out domain-specific services. Measure impact over a few weeks across key metrics like lines of code output, time saved, or accuracy improvements.
Finally, don‘t view AI coding as a replacement for human developers, but as power tools to automate rote tasks and expand what‘s humanly possible. With the right adoption framework, developer productivity stands to massively scale, allowing more focus on complex software innovations.
Exciting times lie ahead in this AI-first era for the future of coding! Let me know if you have any other questions.
