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Top 9 OpenAI Alternatives in 2024
June 12, 2024
Hardik Makadia
CEO, WotNot
When many people think of AI, the first thing that comes to their mind is OpenAI (an AI research laboratory and company founded in 2015).
After all, AI has been at the forefront with products for end-users and tools for businesses. Consumers can chat with ChatGPT as they would with another person and make art with DALL-E. Companies, on the other hand, can access OpenAI’s API to build their custom chatbots and content generators.
But OpenAI isn't the only one doing this. Other OpenAI alternatives might be cheaper, easier to customize, or simpler to use. WotNot is one example that lets you build AI chatbots without knowing how to code.
That’s why we tested a bunch of other alternatives to OpenAI and picked our top nine favorites for you to consider
Key criteria to evaluate OpenAI alternatives
Some of the metrics used to evaluate language models are accuracy, precision, F1 score, and BLEU Score. When considering business-specific factors, compare (also, we compared) alternatives based on:
Performance:
Check for accuracy, speed, and efficiency of each model when delivering results at scale. Key metrics include model accuracy, inference speed, coherence, and subject relevance.
Affordability:
Compare pricing models including cost per API call, monthly fees as well as any extra storage or compute resources charges. Platforms with more flexible “pay-as-you-go” prices with generous free tiers fare better.
Scalability:
The AI infrastructure should be able to expand in tandem with your growing business. Look out for features such as automatic scaling, distributed computing, and efficient resource management.
Accessibility:
Usability is crucial, especially for organizations without strong internal AI competency. Consider aspects like user interface, documentation, and overall simplicity from developers' and non-developers’ perspectives.
Integration:
Ensure your solution fit seamlessly within existing systems and workflows. Study API design, SDK availability, and pre-built integrations with popular frameworks such as TensorFlow or PyTorch.
Customization Options:
Tailor your AI solution to reflect your business needs. Look for options such as custom model training, fine-tuning, and hyperparameter optimization, as well as deployment flexibility (cloud, on-premises, or hybrid).
Community Support:
For trouble-shooting, knowledge exchange, and staying up to date with best practices a robust user community is indispensable. Look for community size, activity level, and existence of forums, tutorials, or other resources.
The 9 best OpenAI alternatives to try in 2024
Here are our top 9 picks for alternatives to OpenAI:
1. Google Gemini
What does it do: Conversational AI
Who is it best for: Google workspace users. Businesses, developers, and users seeking human-like interactions.
Google Gemini, formerly known as Google Bard, is a powerful alternative to OpenAI's ChatGPT, powered by advanced language models such as LaMDA.
With its extensive training on 1.56 trillion words, Gemini offers a robust understanding of user queries and requests, surpassing GPT-4's 13 million token training data.
Unlike a one-size-fits-all approach, Gemini caters to various user groups through distinct offerings:
Free Workspace Integration:
For individual Google Workspace users, Gemini comes included, seamlessly assisting with tasks within Gmail, Docs, and Sheets.
Gemini Business & Enterprise:
Businesses can benefit from advanced capabilities through paid subscription plans. These plans offer increased usage limits, a standalone chat interface for direct interaction with Gemini, and enhanced security features for handling sensitive data (mention specific features if known).
Vertex AI Customization:
Developers and large companies can leverage Vertex AI to fine-tune Gemini models for specific business needs. This allows for highly customized AI solutions that integrate seamlessly into existing workflows.
Features and Capabilities
Gemini boasts a context window of 1 million tokens, maintaining context more effectively throughout longer conversations compared to ChatGPT's 32,000 token limit.
Voice input on both mobile and desktop platforms allows for a more natural, conversational experience.
Seamless integration with Google's ecosystem, including Google Sheets, Google Assistant, and Google apps like Gmail, Docs, Drive, and maps.
Excels at generating creative and nuanced writing while avoiding cliches.
Response time for online searching and information retrieval is approximately three times faster than ChatGPT.
Allows for fine-tuning of models and adaptation to specific use cases, so your developers can tailor the AI to your unique requirements
Is open-source and benefits from a vibrant developer community that contributes to its ongoing development and improvement
Access to a wide range of resources, including documentation, tutorials, and online forums
Use Cases
Gemini's advanced capabilities make it suitable for a wide range of use cases, including content creation, customer support, data analysis, workflow automation, personalized recommendations, language translation, and sentiment analysis.
Limitations
Gemini lags behind in coding and programming tasks, making it less suitable for technical users. Plus, it might not generate accurate images as other AI models do.
Pricing
Free version included with Google Workspace
Advanced plan offers a two-month free trial, followed by a $19.99 monthly subscription.
2. Anthropic
What does it do: Conversational AI
Who is it best for: Businesses and users looking for sophisticated, context-aware AI conversations
Anthropic's Claude is a powerful AI assistant that can engage in conversations, answer questions, and assist with various tasks. Backed by some OpenAI alumni, Claude aims to surpass its competitor, ChatGPT, by delivering highly relevant and informative responses.
Features and Capabilities
Adapts its tone and style to match yours to create a natural and engaging dialogue.
Understands the flow of conversation, and remembers details across a massive 200k token window (roughly 850 pages of text). This allows for superior context awareness and more precise answers.
Compared to ChatGPT, Claude delivers focused outputs rich in information, saving you time.
Users can easily upload and analyze PDFs, images, and other documents to enhance Claude's understanding of the given context.
Has an ability to store pasted data for easier reference and improved conversational flow.
Use Cases
Claude's advanced text generation creates human-like text for various uses, including customer support, data analysis, content creation, and research.
Limitations
Currently, Claude lacks features like plugins, image generation, and code interpretation. Highly technical queries or intricate reasoning may pose difficulties for Claude. Also, users can't edit past prompts within the current conversation.
As a proprietary technology, Claude might be limited in certain regions and lacks the extensive community support and resources of open-source alternatives like Hugging Face.
Pricing
A free version with limited usage
Claude Pro at $20 monthly
Custom API pricing based on the Claude model and the token usage
3. Mistral AI
What does it do: Advanced text generation models
Who is it best for: Businesses and users seeking powerful and flexible AI capabilities for content creation and more.
Mistral AI is a cutting-edge French company that offers state-of-the-art text generation models, providing users with a robust alternative to OpenAI's GPT. Despite having a smaller model size (7 billion parameters) compared to other alternatives, Mistral AI's models deliver the same computational capabilities, allowing for faster text output and more efficient resource utilization.
Features and Capabilities
Offers advanced text generation capabilities, enabling the creation of diverse and high-quality content across various domains
Handles a wide range of language-related tasks, including text summarization, generation, analysis, and classification
Provides Codestral, a 22B parameter, an open-weight model for coding tasks, with training in over 80 different programming languages
Provides a more cost-effective solution compared to larger models, thanks to its efficient architecture and resource utilization
Delivers fast response times and high throughput, making it suitable for real-time applications and large-scale content generation
Supports multiple languages, allowing businesses to cater to diverse audiences and markets
Use Cases
Content Creation: Mistral AI's models excel at generating engaging and contextually relevant content, making them a valuable tool for content marketers, writers, and publishers.
Customer Support: By automating responses and providing accurate information, Mistral AI can streamline customer support processes and improve user satisfaction.
Data Analysis: Mistral AI's text analysis and classification capabilities enable businesses to extract valuable insights from large volumes of unstructured data.
Research and Development: The models can assist in various research tasks, such as literature review, hypothesis generation, and data synthesis
Limitations
As an alternative to OpenAI's GPT, Mistral AI's models may lack some of the advanced features and fine-tuning capabilities offered by larger models. The company's smaller size and relatively newer presence in the market may also result in a less extensive user community and support resources compared to more established players.
Pricing
Mistral AI offers competitive pricing for its text generation models, with both pay-per-use and subscription-based options available.
4. Perplexity AI
What does it do: AI-powered research assistant
Who is it best for: Researchers, academics, and students conducting in-depth research
Perplexity AI is a powerful AI-driven tool that seamlessly blends search engine and chatbot functionalities to deliver in-depth and accurate answers to your inquiries.
Built by a team of ex-Google AI experts, Perplexity AI aims to democratize access to knowledge by making it easier for anyone to learn and explore new topics.
Features and Capabilities
Uses advanced AI models, including OpenAI's GPT-3 and GPT-4, as well as its in-house models, to deliver highly relevant and informative responses
Provides an intuitive user interface that enables users to find information on a wide range of topics easily
Offers various search modes, such as Internet, Academic, and WolframAlpha, allowing users to select the most appropriate sources for their needs
Summarizes articles, web pages, and forum discussions, facilitating quick information retrieval
Pages feature allows generating structured reports on the requested topic, automatically incorporating visuals with easy publishing and sharing.
Provides source citations for all responses, ensuring credibility and proper attribution
Enables users to share their chats with others, fostering collaboration and interactive learning experiences
Use Cases
Perplexity AI is an invaluable tool for researchers, academics, and students conducting in-depth research on various subjects. Its ability to access and summarize information from a wide range of sources, including academic databases, websites, and forums like Reddit, can save users countless hours of manual research.
Limitations
While powerful, Perplexity AI's feature set may be less comprehensive compared to larger AI platforms. If you need highly specialized models for casual conversation, emotional support, or creative brainstorming, explore other options.
Pricing
Perplexity AI offers a free plan with standard features, and Perplexity Pro with advanced functionality at $20/month.
You can also opt for a yearly subscription at $200, which includes a seven-day free trial.
5. Cohere Command R+
What does it do: Streamlines complex production
Who is it best for: Enterprises looking to move beyond proof of concept and into production with complex AI workflows.
Cohere is an advanced AI platform offering powerful, customizable language models tailored to the needs of enterprises and developers. Focused on delivering scalable and efficient AI solutions, Cohere equips users with tools to build and deploy language models for various applications.
Cohere's latest model, Command R+, is designed for conversational interaction and long-context tasks, emphasizing high performance and reliability.
Features and Capabilities
Optimized for complex retrieval augmented generation (RAG) workflows and multi-step tool use (agents)
Trained on a diverse corpus of texts in multiple languages, enabling a wide array of text-generation tasks
Superior performance and reliability, ideal for production-level applications
Supports 10 optimized languages: English, French, Spanish, Italian, German, Brazilian Portuguese, Japanese, Korean, Simplified Chinese, and Arabic
Pre-training data included for an additional 13 languages, expanding its multilingual capabilities
Responds in the user’s language, ensuring seamless cross-lingual communication
Grounds English-language generations using supplied document snippets and includes citations in responses
Capable of multi-step tool use, allowing the model to reason, perform dynamic actions, and adapt based on external information
Use Cases
Building conversational AI applications that require long-context understanding and multi-turn interactions
Developing complex AI workflows involving retrieval augmented generation and multi-step tool use
Creating multilingual AI solutions for a global audience
Implementing AI-powered business processes demanding high performance and reliability
Limitations
Currently, RAG and multi-step tool use (agents) are only available in English. Also, there is a known issue with prompts between 112K - 128K in length resulting in suboptimal generations, which is being addressed by the Cohere team.
Pricing
Pricing for Command R+ is based on a pay-per-use model, with costs varying depending on the specific use case and volume of usage. You may contact Cohere for a customized pricing plan to suit your needs.
6. IBM Watson
What does it do: Enterprise-grade AI and data platform for building, deploying, and managing AI applications
Who is it best for: Businesses looking to scale and accelerate the impact of AI across their organization
IBM Watson is a powerful AI and data platform designed to help enterprises build, deploy, and manage AI applications at scale. With its comprehensive set of tools and services, Watson enables businesses to leverage AI across a wide range of use cases, from customer service and HR to data analysis and decision-making.
Features and Capabilities
watsonx.ai trains, validates, tunes, and deploys machine learning models with ease.
watsonx.data scales analytics and AI workloads for all your data, with an open, hybrid, and governed data store.
watsonx.governance ensures responsible, transparent, and explainable AI workflows.
Pre-built applications for specific business functions, such as customer service (watsonx Assistant), business intelligence (watsonx BI Assistant), and code development (watsonx Code Assistant)
Targeted AI assistants for specific business functions like HR, customer service, or IT operations for faster time-to-value
Strong focus on ethical and regulatory concerns
Uses both proprietary and open-source technologies
Use Cases
IBM Watson can be used for:
Building Q&A resources from proprietary data to share organizational insights
Creating content and deploying chatbots for customer service and support
Coding efficiently and reinventing customer experiences with AI-powered solutions
Deriving insights from large datasets to inform decision-making and strategy
Limitations
IBM Watson has a steep learning curve, particularly for non-technical users. It may be complex for small businesses with limited AI expertise. Some users may even experience difficulties connecting to APIs or integrating with existing systems.
Pricing
IBM Watson offers free trials and basic plans for components like watsonx.ai and watsonx Assistant.
Pay-as-you-go pricing is available for specific services, with custom enterprise pricing based on deployment scope and scale.
7. Stability AI
What does it do: Conversational AI and generative AI for different modalities
Who is it best for: Businesses and developers exploring AI capabilities across different modalities.
Stability AI is a platform that offers a comprehensive suite of cutting-edge AI models for image, video, audio and language. Stability AI stands out when it comes to producing realistic images at high speed and can be used for anything ranging from stock photography to tattoo generation. With flexible and self-hosting options, it enables you to customize your AI needs and seamlessly integrate the technology into your projects and platforms with different models:
Stable Diffusion 3: The most advanced image model, featuring improved performance in multi-subject prompts, image quality, and spelling abilities
SDXL Turbo: Built on the robust foundation of Stable Diffusion XL, this model is designed for ultra-fast performance
Stable Video Diffusion: The first open generative AI video model based on the image model Stable Diffusion, allowing users to generate high-quality videos
Stable Audio 2.0: Generates music and sound effects in high quality using cutting-edge audio diffusion technology
Stable Video 3D: Generates high-quality 3D objects from single images
Stable LM 2 1.6B: A cutting-edge open access language model with deep language comprehension and interpretation capabilities
Features and Capabilities
Performs various language-related tasks, including sentiment analysis and text summarization
Scalable large language model, adaptable to increasing workloads and growing user bases
Open-source models promote transparency and encourage community-driven development
Stable Diffusion is renowned for its exceptional multi-subject image creation capabilities
Stable Assistant combines text and image generation technology to create interactive experiences
Flexible API solutions allow businesses to seamlessly integrate AI services into their platforms
Use Cases
Stability AI's versatile suite of models caters to a wide range of use cases, including high quality image and video creation, music production with sound effects for games, films, and multimedia projects.
Limitations
Pricing structure may be complex due to the dynamic nature and credit-based system.
It provides limited free usage, requiring additional credits for extended or commercial use
Pricing
Stability AI offers a flexible pricing model based on API usage, which requires credits. Initial credits are provided for free, with the option to purchase more as needed to continue using the services.
8. Hugging Face
What does it do: Research and commercial use
Who is it best for: Data scientists, AI enthusiasts, and ML researchers looking to collaborate, create, and share AI applications
Hugging Face is a French-American company founded in 2016 by Clément Delangue, Julien Chaumond, and Thomas Wolf. Initially launched as a chatbot for teenagers, the platform has since evolved into a powerful platform for machine learning (ML) and natural language processing (NLP) applications.
Features and Capabilities
GitHub-like platform to create, share, and collaborate on AI models and datasets
Provides libraries, such as Transformers to develop ML applications
Offers HuggingChat, an open-source AI chatbot with impressive multilingual capabilities
Supports various languages, including English, Spanish, French, and German
All products can be deployed on Amazon Web Services
Offers community support and resources for collaboration and sharing of machine learning models and datasets
Use Cases
Hugging Face is particularly well-suited for developing chatbots and voice assistants, training NLP-based software applications for text analysis and sentiment detection, and creating and deploying AI apps on AWS.
Limitations
HuggingChat, while impressive, may deliver factual errors and occasionally stop generating output mid-response. Some AI applications developed on the platform may require additional fact-checking and refinement. Further, you may need to create a HuggingChat account after submitting a certain number of questions.
Pricing
Hugging Face offers a free, ad-free, open-source chatbot called HuggingChat, with most features accessible without registration.
9. Lightning AI
What does it do: Provides a platform to train, build, and deploy AI with PyTorch Lightning faster and better
Who is it best for: Developers, researchers, and businesses looking to create and deploy AI applications using PyTorch Lightning
Lightning AI is an AI platform founded by William Falcon, the creator of PyTorch Lightning, an open-source Python library that provides a high-level interface for PyTorch. Built on the foundation of PyTorch Lightning, Lightning AI aims to shape the development of artificial intelligence products for both commercial and academic use.
Features and Capabilities
Enables faster and more efficient training, building, and deployment of AI models using PyTorch Lightning
Provides a lightweight and high-performance framework, making deep learning experiments easier to read and reproduce
Offers a user-friendly interface for creating and managing AI projects
Supports the development of generative AI applications, such as text-to-image models
Integrates with popular AI tools and libraries, streamlining the AI development process
Built on the robust foundation of PyTorch Lightning, which is widely adopted and supported by the AI community
Use Cases
You may use Lightning AI for generating AI applications like text-to-image models, for creative and marketing purposes, or conducting academic research and experiments. You may even use it to build and deploy AI-powered products and services for your business.
Limitations
The model is currently in early access stage, with general availability planned for the near future. Plus, it’s not yet open to independent developers, which limits its accessibility.
As a newer platform, Lightning AI may have a smaller user community and fewer resources compared to more established alternatives
Pricing
Lightning AI offers a free tier with 1 active Studio (24/7) and 22 monthly GPU hours. You only pay for what you use by the second and incur no costs when nothing is running.
You can also connect your AWS account to use your cloud credits.
These alternatives offer powerful AI capabilities, but if you’re looking for a more user-friendly solution to create custom AI chatbots and assistants, consider platforms like WotNot - Sign up for a free trial today!
WotNot provides an intuitive drag-and-drop interface, pre-built templates, and seamless integration with popular messaging channels and CRMs, making it easier for businesses to implement conversational AI without extensive coding knowledge.
Future Trends and Innovation
AI is evolving at an unprecedented pace, with new breakthroughs and innovations emerging constantly. As OpenAI and its alternatives continue to push the boundaries of what's possible, we can expect to see exciting developments in several key areas:
1. Multimodal AI:
Integration of text, images, audio, and video into unified AI models, enabling more dynamic and context-aware applications, with platforms like OpenAI's GPT-4.o and DeepFloyd IF already showcasing the potential of multimodal AI.
2. Efficient and Sustainable AI:
Innovations in model compression, quantization, and energy-efficient hardware to reduce the environmental impact of AI, just like Mistral AI.
3. Democratization of AI:
Initiatives like Hugging Face, with its extensive library of pre-trained models and collaborative community, for developers and researchers to experiment with and build upon state-of-the-art AI models. Increasing availability of open-source AI models and platforms
4. AI Governance and Ethics:
With platforms like Anthropic, we can expect to see increased emphasis on transparency, explainability, and fairness in AI models, as well as the development of tools and techniques to detect and mitigate biases and potential misuse.
5. Vertical-Specific AI:
As AI matures, the focus would shift towards vertical-specific AI solutions tailored to particular industries or use cases. Platforms like Cohere, with its focus on enterprise applications, and Stability AI, with its emphasis on creative and multimedia use cases, are examples of this trend.
Final Take
From Google Gemini’s integration with the Google ecosystem to Anthropic’s context-aware conversations, and from Mistral AI’s efficient text generation to Cohere’s enterprise-grade solutions, these OpenAI alternatives provide diverse options.
However, the key lies in carefully evaluating your specific needs and selecting the platform that aligns with your goals and constraints.
Stay informed about the latest AI trends and innovations. Meanwhile, explore how WotNot's AI-powered chatbots and assistants can revolutionize your business.
FAQs
1. How do these alternatives compare to OpenAI?
Each alternative offers unique features and capabilities, making them suitable for different use cases. Factors such as performance, pricing, integration, and community support vary among the alternatives, providing a range of options for businesses.
2. What industries can benefit from these alternatives?
Industries such as healthcare, finance, retail, and customer service can benefit from AI technologies. These alternatives offer solutions tailored to various applications, including data analysis, natural language processing, and automation.
3. How can businesses leverage these alternatives?
You can leverage these alternatives by integrating AI models into their workflows to enhance efficiency, automate tasks, and gain valuable insights from data. Customizable options allow businesses like yours to adapt AI solutions to their specific needs.
4. What considerations should businesses keep in mind when choosing an Open AI alternative?
Businesses should consider factors such as performance, affordability, scalability, integration capabilities, and community support. Evaluating these criteria will help in selecting the most suitable AI solution.
5. How can businesses get started with implementing these alternatives?
Businesses can start by identifying their specific AI needs and exploring the features and capabilities of each alternative. Utilizing free tiers and trial periods can provide hands-on experience. Consulting with AI experts and leveraging community resources can also facilitate implementation.
ABOUT AUTHOR
Hardik Makadia
CEO, WotNot
His leadership, pioneering vision, and relentless drive to innovate and disrupt has made WotNot a major player in the industry.