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ChatGPT Alternatives FREE 2024 (Try These FREE AI chatbots)

Looking for alternatives to ChatGPT?

Discover the top AI-powered platforms for coding, natural language processing, and writing, including open-source options, Google alternatives, and free online tools. Explore the pros and cons of each platform and find the best fit for your needs

ChatGPT is a large language model developed by OpenAI that uses artificial intelligence to simulate human-like conversations.

Let’s explore this article and get the best AI Chatbot that can answer your questions easily and correctly among the listed top 28 ChatGPT alternatives.

We can say it is a great Open Ai, but this also has some capacity, only limited people use it at a time.

That is why we come up with some best Ai tools and software that work the same as ChatGPT.

So, you can choose the best option for you.

Let’s Start!!

What is ChatGPT?

ChatGPT is a language model developed by OpenAI that can generate human-like responses to a wide range of prompts, questions, and conversation topics.

It is very important to know what actually ChapGPT is because many of you think that ChatGPT is just a Chatbot that can provide you answer to your every question, but This is just a feature of ChatGPT, so lets me explain thing in more detail.

About ChatGPT

It has been trained on a large dataset of text from the internet and can provide answers to questions, write essays, summarize articles, and even generate creative writing. ChatGPT is designed to mimic human language use and can adapt to different writing styles and tones.

Tools like ChatGPT has completely removed, Article Spinner tools from the market. Because AI content creator tools create new content, that is optimized too.

Why People Searching for Other Options-

What Things Are Missing From ChatGPT?

There is no way to say that ChatGPT is not a better Ai Chatbot, but still, there are some points that we want to consider ChatGPT needs to Improve.

Here we are sharing some limitations of ChatGPT:

  • Limited output length: Compared to some other content generators, ChatGPT has a relatively short maximum output length, which can limit its usefulness for certain applications.
  • Less control over output: ChatGPT’s output is generated autonomously, which means that users have less control over the specific content that it generates as compared to other content generators that allow for more user input.
  • Higher resource usage: ChatGPT requires a lot of computational resources to generate content, which can make it more expensive and time-consuming to use as compared to some other content generators.
  • Lower customization options: Compared to some other content generators, ChatGPT offers fewer options for customization, such as formatting or styling.
  • Limited image or video generation: ChatGPT’s primary output is text-based, which means that it may not be as useful for generating visual content such as images or videos as compared to other content generators.
  • Limited domain knowledge: ChatGPT’s output is limited by the data it has been trained on, which can make it less useful for generating content on niche or specialized topics as compared to other content generators that are specifically designed for those domains.
  • Potential for repetitive output: Because ChatGPT generates output based on patterns in its training data, it may be more prone to generating repetitive content than some other content generators.
  • Limited ability to learn from user input: ChatGPT’s ability to learn from user input and improve its output over time is limited as compared to some other content generators that use machine learning or other advanced techniques.
  • Less suitable for long-form content: ChatGPT’s short maximum output length may make it less suitable for generating longer-form content such as articles or reports as compared to other content generators that allow for longer output.
  • Limited ability to generate structured content: ChatGPT’s output is primarily text-based, which means that it may be less useful for generating structured content such as forms or templates as compared to other content generators that are designed specifically for those use cases.

So if we consider these cons, we should check the ChatGPT Alternatives here and most of them are free.

Mentioned Category wised-

Table of ChatGPT Alternatives (Category-wise)

Best Chatbot PlatformsThere are several chatbot platforms available, each with its own strengths and weaknesses. Some of the most popular ones include Dialogflow, Amazon Lex, Microsoft Bot Framework, and IBM Watson Assistant. The best one for you will depend on your specific needs and requirements.
Alternatives to ChatGPT for CodingSome alternatives to ChatGPT for coding include CodeGPT, Codex by OpenAI, and Kite. These platforms use AI to assist with coding tasks, similar to ChatGPT.
Free online Alternatives to ChatGPTSome free online alternatives to ChatGPT include Replika, Cleverbot, and Mitsuku. These platforms use natural language processing to simulate conversations with users, although they may not be as advanced as ChatGPT.
Open-source Alternatives to ChatGPTOne open-source alternative to ChatGPT is GPT-Neo, which is a community-driven project that aims to create a large language model similar to GPT-3. Other options include DialoGPT and EleutherAI’s GPT models.
Google Alternatives to ChatGPTGoogle has several AI-powered platforms that could be seen as alternatives to ChatGPT, including Google Assistant, Google Dialogflow, and Google Cloud AI Platform. However, these platforms may require more technical expertise to set up and use compared to ChatGPT.
Alternatives to ChatGPT for essaysWhile ChatGPT is primarily designed for natural language conversations, there are several AI-powered writing tools available that could be used as alternatives for essays. Some popular ones include Grammarly, ProWritingAid, and Hemingway Editor. These platforms can help with tasks like grammar checking, style editing, and overall clarity of writing.

Choose The Best Option For You-

25 Best FREE AI Chatbots Like ChatGPT

There are several other language models and chatbot applications that are similar to ChatGPT, including GPT-2 and GPT-3, which are also developed by OpenAI.

Other similar apps include IBM Watson, Google AI, and Amazon Lex. These applications are all designed to generate natural language responses and provide assistance with a wide range of tasks, from answering customer service inquiries to creating content for marketing campaigns.

1

IBM Watson

IBM Watson is a suite of artificial intelligence and cognitive computing technologies that includes machine learning, natural language processing, and data analytics capabilities.

IBM Watson Chatbot

Some of its features include:

  1. Language Understanding: Watson can understand and analyze human language, including idioms and slang.
  2. Speech to Text: Watson can transcribe speech to text in real time.
  3. Text to Speech: Watson can convert text into natural-sounding speech.
  4. Visual Recognition: Watson can analyze images and videos to recognize objects, faces, and scenes.
  5. Personality Insights: Watson can analyze text to understand an individual’s personality traits, needs, and values.
  6. Discovery: Watson can analyze unstructured data, such as documents and web pages, to extract insights and trends.
  7. Assistant: Watson can provide personalized customer support and answer frequently asked questions.
  8. Knowledge Studio: Watson can train and deploy custom machine-learning models to solve specific business problems.

Overall, IBM Watson is a powerful and versatile tool that can be used in a variety of industries, including healthcare, finance, and customer service. and this is why we mentioned IBM in the list of best ChatGPT Alternatives.

2

Google Bard AI

Bard AI is a natural language generation platform that uses advanced AI and machine learning algorithms to generate human-like written content at scale.

Some of its features include:

  1. Content Automation: Bard AI can generate high-quality written content, such as product descriptions, blog posts, and social media posts, without human intervention.
  2. Multilingual Support: Bard AI can generate content in multiple languages, including English, Spanish, French, and German.
  3. SEO Optimization: Bard AI can optimize generated content for search engines to improve its visibility and ranking.
  4. Tone and Style: Bard AI can generate content that matches a specific tone and style, such as informative, persuasive, or entertaining.
  5. Customization: Bard AI can be trained on specific datasets and customized to generate content that meets specific business needs and goals.

Overall, Bard AI is a powerful tool for businesses and content creators looking to generate high-quality written content at scale. It can save time and resources while improving the overall quality and consistency of content.

ChatGPT vs Google Bard

ChatGPT and Google Bard are two popular AI language models used in natural language processing. ChatGPT is a general-purpose model that generates contextually appropriate responses to a wide range of input, using unsupervised learning.

However, its limited domain-specific knowledge and interpretability may make it less effective for specialized industries or fields. In contrast, Google Bard Ai is a more specialized model designed to understand specific contexts and generate content specific to certain fields, using supervised learning.

But its training data is restricted to a specific domain, which may limit its versatility in other domains. Ultimately, the choice of model depends on the specific needs of the application and the type of content that needs to be generated.

3

Amazon Lex

Amazon Lex is another AI like ChatGPT, It is a service that enables developers to build conversational interfaces, or chatbots, using voice and text. It uses natural language understanding and automatic speech recognition to enable a wide range of interactions between users and applications.

Amazon Lex Chatbot

Some of its features include:

  1. Automatic Speech Recognition: Amazon Lex can convert speech to text, enabling users to interact with the chatbot using voice.
  2. Natural Language Understanding: Amazon Lex can understand the intent and context of user input, enabling it to provide appropriate responses.
  3. Multi-turn Conversations: Amazon Lex can maintain context across multiple turns of the conversation, enabling it to provide more accurate and personalized responses.
  4. Integration with Other AWS Services: Amazon Lex can be integrated with other AWS services, such as Amazon S3, Lambda, and DynamoDB, to enable more complex interactions.
  5. Multi-platform Support: Amazon Lex can be deployed on a variety of platforms, including web, mobile, and messaging applications.
  6. Customization: Amazon Lex can be customized using pre-built templates and tools, or by building custom conversational flows.

Overall, Amazon Lex is a powerful tool for building conversational interfaces that can improve the user experience of applications and services. It can be used in a variety of industries, including healthcare, finance, and customer service.

4

RoBERTa

RoBERTa (Robustly Optimized BERT Pretraining Approach) is a language model developed by Facebook AI Research (FAIR) based on the BERT architecture. It was trained on a massive amount of text data to improve its ability to understand and generate natural language text. Some of its features include:

  1. Large Training Dataset: RoBERTa was trained on a massive dataset of diverse text sources, including books, web pages, and Wikipedia, to improve its ability to understand and generate natural language text.
  2. Better Pre-training Techniques: RoBERTa uses advanced pre-training techniques such as dynamic masking and larger batch sizes to improve the model’s performance.
  3. High Performance: RoBERTa has achieved state-of-the-art results on several natural language processing tasks, including sentiment analysis, named entity recognition, and question-answering.
  4. Transfer Learning: RoBERTa can be fine-tuned on smaller datasets for specific natural language processing tasks, making it a versatile and efficient tool for a wide range of applications.
  5. Open-Source: RoBERTa is open-source and available to the research community, allowing for further development and improvement of natural language processing techniques.

Overall, RoBERTa is a powerful and versatile language model that has significantly advanced the state of the art in natural language processing. Its large training dataset and advanced pre-training techniques have enabled it to achieve state-of-the-art results on a wide range of natural language processing tasks.

5

Meena by Google

Meena is a state-of-the-art open-domain chatbot developed by Google using advanced neural networks and natural language processing techniques. It is another best alternative to the ChatGPT to try to get answers.

Meena by Google

It was designed to be more conversational and engaging than previous chatbots, with the goal of creating a more human-like experience.

Some of its features include:

  1. Large Training Dataset: Meena was trained on a large and diverse dataset of real-world conversations to improve its ability to understand and respond to a wide range of topics.
  2. Multi-Turn Conversations: Meena is able to maintain context across multiple turns of the conversation, allowing for more natural and engaging interactions.
  3. Empathy and Personality: Meena was designed to have a more human-like personality and the ability to show empathy and emotion, making interactions more relatable and engaging.
  4. Open-Domain: Meena is able to respond to a wide range of topics and questions, making it a versatile chatbot for a variety of use cases.
  5. Evaluation Metrics: Meena was evaluated using new metrics that better measure its ability to engage in high-quality conversations, including Sensibleness and Specificity Average (SSA) and the recently introduced Hugging Face’s Generation Likelihood (GL).

Overall, Meena represents a significant advancement in chatbot technology, with a focus on creating more engaging and human-like interactions. this works Similarly To ChatGPT.

6

XLNet

XLNet is a language model developed by Google AI researchers that uses a generalized autoregressive pretraining method to improve its ability to understand and generate natural language text.

It was designed to overcome the limitations of other language models, such as BERT, by using a permutation-based training approach. Some of its features include:

  1. Generalized Autoregressive Pretraining: XLNet uses a generalized autoregressive pretraining method that models all possible permutations of the input sequence, improving its ability to handle complex language structures.
  2. Larger Context: XLNet is able to model longer contexts than previous language models, enabling it to better understand and generate natural language text.
  3. Improved Performance: XLNet has achieved state-of-the-art results on a range of natural language processing tasks, including question-answering, sentiment analysis, and text classification.
  4. Transfer Learning: XLNet can be fine-tuned on smaller datasets for specific natural language processing tasks, making it a versatile and efficient tool for a wide range of applications.
  5. Open-Source: XLNet is open-source and available to the research community, allowing for further development and improvement of natural language processing techniques.

Overall, XLNet represents a significant advancement in natural language processing technology, with a focus on overcoming the limitations of previous models and improving performance on a wide range of tasks.

Its generalized autoregressive pretraining method and ability to model longer contexts enable it to better understand and generate natural language text, making it a powerful tool for a variety of applications. and this is why we mentioned XLNet in the list of best ChatGPT Alternatives.

7

ChatSonic by WriteSonic

ChatSonic is a chatbot-building platform developed by Writesonic, a company that specializes in AI writing tools. It uses natural language processing (NLP) technology to enable users to create chatbots for a variety of use cases without requiring any coding experience.

WriteSonic’s ChatSonic is a very popular ChatGPT alternative, Its ChatSonic is more advanced as compared to the Open AI’s WriteSonic.

Chatsonic by writesonic

Some of its features include:

  1. Easy-to-Use Interface: ChatSonic has a user-friendly interface that enables users to create chatbots easily and quickly.
  2. Customizable Templates: ChatSonic provides customizable chatbot templates for a range of use cases, including customer support, lead generation, and sales.
  3. AI-Powered: ChatSonic uses natural language processing (NLP) technology to enable chatbots to understand and respond to user inquiries in a natural and conversational way.
  4. Multi-Channel Support: ChatSonic chatbots can be deployed on a range of channels, including websites, social media platforms, and messaging apps.
  5. Analytics and Insights: ChatSonic provides analytics and insights into chatbot performance, including metrics such as engagement rates and user satisfaction.

Overall, ChatSonic is a powerful and easy-to-use chatbot-building platform that leverages the power of AI to create conversational and engaging chatbot experiences.

It’s customizable templates and multi-channel support make it a versatile tool for a range of use cases, while its analytics and insights provide valuable information for optimizing chatbot performance.

8

DialoGPT

DialoGPT (Dialogue Generative Pre-trained Transformer) is a large-scale generative language model developed by Microsoft Research Asia.

It is based on the GPT architecture and was pre-trained on a massive amount of conversational data to improve its ability to generate human-like responses in natural language conversations.

Some of its features include:

  1. Conversational Understanding: DialoGPT is designed to understand and generate natural language in a conversational context, making it well-suited for building chatbots or dialogue systems.
  2. Large-Scale Training: DialoGPT was pre-trained on a massive dataset of conversational data, enabling it to understand a wide range of conversational patterns and generate responses that are contextually relevant.
  3. High Performance: DialoGPT has achieved state-of-the-art results on several natural language processing benchmarks, including the Conversational Intelligence Challenge.
  4. Transfer Learning: DialoGPT can be fine-tuned on smaller datasets for specific dialogue tasks, making it a versatile and efficient tool for building dialogue systems and chatbots.
  5. Open-Source: DialoGPT is open-source and available to the research community, allowing for further development and improvement of natural language processing techniques.

Overall, DialoGPT is a powerful and versatile language model that has significantly advanced the state of the art in natural language processing for dialogue systems and chatbots.

It’s large-scale training and conversational understanding make it well-suited for building chatbots, while its transfer learning capabilities enable it to be adapted to a wide range of dialogue tasks.

9

CoPilot

CoPilot is an AI-powered code completion tool developed by OpenAI. It is designed to assist software developers in writing code more quickly and efficiently by suggesting code snippets, functions, and other programming constructs based on the context of the code being written.

Some of its features include:

  1. Contextual Code Suggestions: CoPilot uses machine learning to analyze the context of the code being written and suggest relevant code snippets, functions, and other programming constructs.
  2. Multimodal Input: CoPilot supports a variety of input modes, including natural language queries and code snippets, allowing developers to interact with it in the way that feels most natural to them.
  3. Code Generation: CoPilot can generate entire code files from a natural language description of the desired functionality, allowing developers to quickly create new code based on high-level descriptions.
  4. Personalization: CoPilot can learn from the code patterns and preferences of individual developers, providing more personalized and relevant code suggestions over time.
  5. Integration with Popular IDEs: CoPilot integrates with popular integrated development environments (IDEs) such as Visual Studio Code, allowing developers to use it seamlessly as part of their regular coding workflow.

Overall, CoPilot is a powerful tool for software developers that can significantly improve their productivity and efficiency by providing intelligent and contextually relevant code suggestions.

Its ability to learn from individual developer patterns and preferences makes it a particularly valuable tool for developers who work on complex or large-scale software projects. and this is why we mentioned COPilot in the list of best ChatGPT Alternatives.

10

Tabnine

Tabnine is an AI-powered code completion tool that uses machine learning algorithms to provide intelligent code suggestions to software developers. Some of its key features include:

Tabnine Chatbot
  1. Contextual Code Suggestions: Tabnine uses machine learning to analyze the context of the code being written and suggest relevant code snippets, functions, and other programming constructs.
  2. Multimodal Input: Tabnine supports a variety of input modes, including natural language queries and code snippets, allowing developers to interact with it in the way that feels most natural to them.
  3. Cross-Platform Support: Tabnine supports a wide variety of programming languages and integrates with many popular integrated development environments (IDEs), including Visual Studio Code, JetBrains, and Sublime Text.
  4. Personalization: Tabnine can learn from the code patterns and preferences of individual developers, providing more personalized and relevant code suggestions over time.
  5. Code Generation: Tabnine can generate entire code files from a natural language description of the desired functionality, allowing developers to quickly create new code based on high-level descriptions.
  6. Fast and Lightweight: Tabnine is designed to be fast and lightweight, with a small memory footprint and low CPU usage.

Overall, Tabnine is a powerful tool that can significantly improve the productivity and efficiency of software developers by providing intelligent and contextually relevant code suggestions.

Its ability to learn from individual developer patterns and preferences, as well as its support for a wide variety of programming languages and platforms, make it a valuable tool for developers of all kinds.

11

Elsa Speaks

Elsa Speaks is an AI-powered text-to-speech (TTS) voice assistant developed by Google’s Speech Technologies team. It is designed to convert written text into natural-sounding speech in a variety of languages and voices.

Some of its key features include:

  1. Multilingual Support: Elsa Speaks supports a wide variety of languages, including English, Spanish, French, German, Italian, Japanese, and many others.
  2. Multiple Voices: Elsa Speaks offers multiple voices for each language, giving users the ability to choose the voice that best fits their needs.
  3. High-Quality Audio: Elsa Speaks uses advanced speech synthesis algorithms to produce natural-sounding, high-quality audio.
  4. Customization Options: Elsa Speaks allows users to customize the speed, pitch, and volume of the synthesized speech, as well as add pauses and other effects to create a more natural-sounding voice.
  5. Simple Integration: Elsa Speaks can be easily integrated into a wide variety of applications and devices, including chatbots, virtual assistants, and other voice-enabled technologies.

Overall, Elsa Speaks is a powerful TTS tool that can significantly improve the user experience of applications and devices that rely on synthesized speech.

Its support for a wide variety of languages and voices, along with its high-quality audio and customization options, make it a valuable tool for developers and users alike.

12

DeepL

DeepL is an AI-powered language translation service that uses neural machine translation algorithms to provide high-quality translations in a variety of languages. Some of its key features include:

DeepL Chatbot
  1. High-Quality Translations: DeepL uses advanced neural machine translation algorithms to produce high-quality translations that are often more accurate than other machine translation services.
  2. Wide Language Support: DeepL supports a wide variety of languages, including English, Spanish, French, German, Italian, Dutch, Polish, Russian, and many others.
  3. Customizable Translation Quality: DeepL allows users to customize the translation quality based on their needs, with options ranging from a fast and rough translation to a slow and precise one.
  4. Integration with Other Tools: DeepL can be easily integrated with other tools and platforms, including web browsers, Microsoft Office, and popular content management systems like WordPress.
  5. User-Friendly Interface: DeepL’s user interface is designed to be simple and intuitive, with a clean and easy-to-use interface that makes it easy for users to translate text quickly and efficiently.

Overall, DeepL is a powerful language translation tool that can significantly improve the accuracy and efficiency of translations for users and businesses.

Its support for a wide variety of languages, customizable translation quality, and easy integration with other tools make it a valuable tool for anyone who needs to translate text on a regular basis.

13

Dialogflow

Dialogflow is a natural language processing (NLP) platform developed by Google. It allows developers to build conversational interfaces for a variety of applications such as chatbots, voice assistants, and customer service bots.

Features of Dialogflow include:

  1. Natural Language Understanding: Dialogflow uses machine learning algorithms to analyze user input and understand the intent behind it.
  2. Multi-Platform Support: Dialogflow allows developers to create chatbots and voice assistants for a variety of platforms including Google Assistant, Amazon Alexa, Facebook Messenger, and more.
  3. Integration with other Google Services: Dialogflow can be integrated with other Google services such as Google Cloud Speech-to-Text, Google Cloud Text-to-Speech, and Google Analytics.
  4. Customizable Responses: Dialogflow provides developers with the ability to customize the responses of their chatbots, voice assistants, and customer service bots based on the intent of the user.
  5. User Management: Dialogflow allows developers to manage their users and their interactions with the chatbot or voice assistant.
  6. Pre-built Templates: Dialogflow provides developers with pre-built templates for common use cases, making it easier to build chatbots and voice assistants.
  7. Analytics: Dialogflow provides developers with analytics to help them understand how their chatbot or voice assistant is being used and identify areas for improvement.

Overall, Dialogflow is a powerful platform that provides developers with the tools they need to build sophisticated conversational interfaces for a variety of applications. and this is the reason Why we are considering Dialogflow in the list of best ChatGPT Alternatives.

14

ELMo

ELMo, which stands for Embeddings from Language Models, is a deep contextualized word representation model developed by the Allen Institute for AI (AI2) as part of the AllenNLP (Natural Language Processing) project.

It is a neural network-based approach to generate word embeddings, which are fixed-size vector representations of words.

What sets ELMo apart from traditional word embedding techniques like Word2Vec and GloVe is that it generates dynamic, context-dependent representations of words, rather than fixed ones.

ELMo considers the entire sentence and the surrounding context to generate the word embedding, which allows it to capture the nuances of meaning that depend on context.

Some key features of ELMo are:

  • Deep contextualized representations: The word embeddings generated by ELMo take into account the entire sentence and the surrounding context, allowing it to capture the meaning that depends on context.
  • High-quality word representations: ELMo word embeddings have been shown to outperform other state-of-the-art techniques on various natural language processing tasks, including sentiment analysis, text classification, and named entity recognition.
  • Pre-trained models available: ELMo models have been pre-trained on large corpora of text and are publicly available for download, allowing researchers and developers to use them in their own projects.
  • Integration with other NLP tools: ELMo embeddings can be used as input to other NLP models, such as neural machine translation and question-answering systems, to improve their performance.

ELMo is a powerful tool for natural language processing and has found applications in various areas, such as sentiment analysis, text classification, and language translation.

15

SpaCy

SpaCy is an open-source natural language processing (NLP) library written in Python. It is designed to be efficient, easy to use, and scalable.

Spacy Chatbot

Some of the key features of SpaCy include:

  1. Linguistic Analysis: SpaCy provides a range of linguistic annotations, such as tokenization, named entity recognition (NER), and part-of-speech (POS) tagging.
  2. Pre-trained Models: SpaCy provides pre-trained models for a range of NLP tasks, such as NER and POS tagging. These models can be used as-is or fine-tuned for a specific application.
  3. Customizable Pipelines: SpaCy allows users to create their own custom pipelines, including adding custom models or algorithms.
  4. Easy Integration: SpaCy is designed to be easy to integrate with other Python libraries, including machine learning frameworks like TensorFlow and PyTorch.
  5. Fast and Efficient: SpaCy is designed to be fast and efficient, making it suitable for processing large amounts of text.
  6. Support for Multiple Languages: SpaCy supports multiple languages, including English, German, Spanish, French, Italian, Dutch, and Portuguese.
  7. Active Community: SpaCy has an active community of developers and users, with regular updates and new features being added.

Overall, SpaCy is a powerful and flexible NLP library that is suitable for a wide range of applications. Its pre-trained models, customizable pipelines, and support for multiple languages make it a popular choice for NLP tasks such as text classification, sentiment analysis, and more.

16

NLTK

NLTK (Natural Language Toolkit) is a Python library for working with human language data. It provides a wide range of tools for tasks such as text classification, tokenization, stemming, tagging, parsing, and semantic analysis.

Some key features of NLTK are:

  • A comprehensive collection of language processing tools: NLTK provides a range of language processing tools for text classification, tokenization, stemming, tagging, parsing, and semantic analysis, making it a versatile tool for various NLP tasks.
  • Easy-to-use interfaces: NLTK provides user-friendly interfaces for using its tools and models, making them accessible to users with different levels of expertise.
  • Wide range of language models: NLTK provides access to various pre-trained models for different languages, making it easier to process and analyze text data in different languages.
  • Robust community support: NLTK has a large and active community of developers and users who contribute to its development and support.
  • Open source and free to use: NLTK is an open-source project, which means it is free to use, modify, and distribute.

NLTK is widely used in natural language processing research and education, and it has found applications in various areas, such as sentiment analysis, language translation, and text classification.

17

TensorFlow

TensorFlow is an open-source machine learning library developed by the Google Brain team. It is designed to make it easy to build and train deep learning models for a wide range of tasks, from image and speech recognition to natural language processing and reinforcement learning.

Some key features of TensorFlow are:

  • Flexible architecture: TensorFlow provides a flexible architecture for building and training different types of deep learning models, including neural networks, convolutional neural networks, recurrent neural networks, and others.
  • Distributed computing: TensorFlow can be used to distribute model training across multiple CPUs or GPUs, allowing users to train larger and more complex models.
  • High-level APIs: TensorFlow provides high-level APIs for building and training deep learning models, such as Keras and Estimators, making it easier for users to get started with deep learning.
  • Visualization tools: TensorFlow provides visualization tools to help users understand the behavior of their models during training and debug any issues.
  • Serving and deployment: TensorFlow provides tools for deploying trained models in production, making it easier to integrate deep learning models into real-world applications.

TensorFlow is widely used in industry and academia for a wide range of applications, including image and speech recognition, natural language processing, recommender systems, and robotics.

It is considered one of the most popular and widely used machine learning libraries, with a large and active community of developers and users.

18

Rasa

Rasa is an open-source framework for building conversational AI chatbots. It is designed to be flexible, scalable, and easy to use.

Rasa Chatbot

Some of the key features of Rasa include:

  1. Natural Language Understanding (NLU): Rasa provides NLU capabilities that allow chatbots to understand user messages and extract intent and entities.
  2. Dialog Management: Rasa provides tools for managing conversations with users, including handling multi-turn conversations and handling contextual information.
  3. Open-Source and Customizable: Rasa is an open-source framework that can be customized to suit a wide range of use cases.
  4. Multilingual Support: Rasa supports multiple languages, including English, Spanish, French, German, and more.
  5. Integration with Multiple Channels: Rasa can be integrated with multiple channels, including Facebook Messenger, Slack, and others.
  6. Machine Learning Capabilities: Rasa includes machine learning capabilities for training and optimizing chatbots.
  7. Community and Support: Rasa has an active community of developers and users, with regular updates and new features being added.

Overall, Rasa is a powerful and flexible framework for building conversational AI chatbots. Its NLU and dialog management capabilities, along with its support for multiple languages and channels, make it a popular choice for businesses and developers looking to build chatbots for a wide range of use cases.

19

PyTorch

PyTorch is an open-source machine-learning framework written in Python. It is designed to be flexible, efficient, and easy to use. Some of the key features of PyTorch include:

  1. Dynamic Computation Graph: PyTorch uses a dynamic computation graph, which allows for more flexibility and easier debugging compared to a static computation graph.
  2. Easy to Use: PyTorch is designed to be easy to use, with a simple and intuitive API that makes it easy to build and train machine learning models.
  3. Fast and Scalable: PyTorch is designed to be fast and scalable, making it suitable for processing large amounts of data and building complex models.
  4. Neural Network Building Blocks: PyTorch provides a range of building blocks for building neural networks, including layers, activation functions, loss functions, and optimizers.
  5. Support for Multiple Devices: PyTorch supports multiple devices, including CPUs, GPUs, and TPUs, allowing for efficient computation on a range of hardware.
  6. Community and Support: PyTorch has an active community of developers and users, with regular updates and new features being added.
  7. Integration with Other Libraries: PyTorch can be easily integrated with other Python libraries, such as NumPy and SciPy.

Overall, PyTorch is a powerful and flexible machine-learning framework that is suitable for a wide range of applications.

Its easy-to-use API, dynamic computation graph, and support for multiple devices make it a popular choice for researchers, developers, and data scientists looking to build and train machine-learning models.

20

Amazon Comprehend

Amazon Comprehend is a natural language processing (NLP) service provided by Amazon Web Services (AWS). It enables developers to easily integrate NLP capabilities into their applications without requiring expertise in machine learning or NLP.

Amazon Comprehend Chatbot

Some key features of Amazon Comprehend are:

  • Text analysis: Amazon Comprehend can analyze text for sentiment, key phrases, entities, language, syntax, and other types of information, making it easier to extract insights from large amounts of text data.
  • Custom entity recognition: Amazon Comprehend allows users to train custom entity recognition models using their own data, enabling them to recognize and extract specific types of entities from text, such as product names or people’s names.
  • Real-time and batch processing: Amazon Comprehend can process text in real-time as it is being generated, or in batch mode for large amounts of existing text data.
  • Multi-language support: Amazon Comprehend supports a wide range of languages, including English, Spanish, French, German, Italian, Portuguese, and Japanese.
  • Integration with other AWS services: Amazon Comprehend can be integrated with other AWS services, such as Amazon S3, Amazon DynamoDB, and Amazon Elasticsearch, allowing users to easily analyze text data stored in these services.

Amazon Comprehend is commonly used for a wide range of applications, such as customer service analytics, social media monitoring, content categorization, and compliance analysis.

It offers various pricing plans based on the volume of text processed and the types of analysis performed, with a free tier available for up to 25,000 units of text processed per month for the first 12 months. and this is why you should pick Amazon Comprehend from the list of best ChatGPT Alternatives.

21

Stanford CoreNLP

Stanford CoreNLP is a suite of natural language processing tools developed by the Stanford Natural Language Processing Group.

It provides a wide range of tools for tasks such as tokenization, part-of-speech tagging, parsing, named entity recognition, sentiment analysis, and coreference resolution. Some key features of Stanford CoreNLP are:

  • A comprehensive set of NLP tools: Stanford CoreNLP provides a comprehensive set of NLP tools for various tasks, making it a versatile tool for processing and analyzing text data.
  • Support for multiple languages: Stanford CoreNLP supports multiple languages, including English, Spanish, French, German, Arabic, and Chinese.
  • High accuracy: Stanford CoreNLP is known for its high accuracy, thanks to its use of machine learning algorithms and deep linguistic analysis.
  • Integration with other tools: Stanford CoreNLP can be integrated with other NLP tools, such as WordNet and GloVe, to enhance its performance and accuracy.
  • Open source and free to use: Stanford CoreNLP is an open-source project, which means it is free to use, modify, and distribute.

Stanford CoreNLP is widely used in natural language processing research and education, as well as in various industries, such as finance, healthcare, and marketing. It has found applications in various areas, such as sentiment analysis, language translation, and text classification.

It can be used as a standalone tool or as part of a larger NLP pipeline, and it can be accessed through a variety of programming languages, including Java, Python, and Ruby.

22

Hugging Face Transformers

Hugging Face Transformers is an open-source library that provides a range of natural language processing capabilities, including language modeling, machine translation, and question-answering.

It is designed to be easy to use and integrate into existing machine learning workflows.

Hugging Face Transformers Chatbot

Some of the key features of Hugging Face Transformers include:

  1. Pre-trained Models: Hugging Face Transformers provides pre-trained models for a range of natural language processing tasks, such as sentiment analysis, named entity recognition, and machine translation.
  2. Easy-to-Use API: Hugging Face Transformers provides a simple and intuitive API that makes it easy to use and integrate into existing machine-learning workflows.
  3. Fine-Tuning Capabilities: Hugging Face Transformers allows developers to fine-tune pre-trained models on their specific datasets, allowing for improved performance on specific tasks.
  4. State-of-the-Art Performance: Hugging Face Transformers models have achieved state-of-the-art performance on a range of natural language processing benchmarks.
  5. Multilingual Support: Hugging Face Transformers supports multiple languages, including English, Spanish, French, German, and more.
  6. Active Community: Hugging Face Transformers has an active community of developers and users, with regular updates and new models being added.
  7. Integration with Other Libraries: Hugging Face Transformers can be easily integrated with other Python libraries, such as PyTorch and TensorFlow.

Overall, Hugging Face Transformers is a powerful and flexible library for natural language processing. Its pre-trained models, fine-tuning capabilities, and state-of-the-art performance make it a popular choice for researchers, developers, and data scientists looking to build and train machine-learning models for a wide range of NLP tasks.

23

Apache OpenNLP

Apache OpenNLP is an open-source natural language processing (NLP) library written in Java. It provides a set of tools for various NLP tasks, such as tokenization, part-of-speech tagging, named entity recognition, parsing, and coreference resolution.

Some key features of Apache OpenNLP are:

  • A comprehensive set of NLP tools: Apache OpenNLP provides a comprehensive set of NLP tools for various tasks, making it a versatile tool for processing and analyzing text data.
  • High accuracy: Apache OpenNLP is known for its high accuracy, thanks to its use of machine learning algorithms and deep linguistic analysis.
  • Support for multiple languages: Apache OpenNLP supports multiple languages, including English, German, Spanish, and Dutch.
  • Integration with other Apache tools: Apache OpenNLP can be integrated with other Apache tools, such as Apache Solr and Apache Tika, to enhance its functionality and performance.
  • Customizable: Apache OpenNLP allows users to train their own models using their own data, enabling them to customize the NLP tools to their specific needs.

Apache OpenNLP is widely used in various industries, such as finance, healthcare, and marketing, as well as in natural language processing research and education. It has found applications in various areas, such as sentiment analysis, language translation, and text classification.

It can be accessed through a variety of programming languages, including Java, Python, and Ruby. Since it is open source, it is free to use, modify, and distribute.

24

Lexalytics

Lexalytics is a natural language processing (NLP) company that provides a range of software solutions for text analytics and sentiment analysis.

Lexalytics chatbot

Its core product is Salience, which is a text analytics engine that provides a suite of NLP tools for various tasks, such as sentiment analysis, entity recognition, summarization, and topic extraction.

Some key features of Lexalytics and Salience are:

  • High accuracy: Lexalytics is known for its high accuracy, thanks to its use of machine learning algorithms and deep linguistic analysis.
  • Support for multiple languages: Salience supports multiple languages, including English, Spanish, French, German, Italian, and Portuguese.
  • A comprehensive set of NLP tools: Salience provides a comprehensive set of NLP tools for various tasks, making it a versatile tool for processing and analyzing text data.
  • Customizable: Salience allows users to train their own models using their own data, enabling them to customize the NLP tools to their specific needs.
  • Integration with other tools: Salience can be integrated with other tools, such as Excel, Tableau, and Hadoop, to enhance its functionality and performance.
  • Cloud-based and on-premises deployment: Salience can be deployed in the cloud or on-premises, depending on the user’s needs.

Lexalytics and Salience are widely used in various industries, such as social media monitoring, customer experience management, and market research. They have found applications in various areas, such as sentiment analysis, social media analytics, and voice-of-customer analysis.

They offer various pricing plans based on the volume of text processed and the types of analysis performed, with a free trial available for testing the product.

25

Indico

Indico is a cloud-based natural language processing (NLP) platform that provides a range of NLP capabilities, including text classification, sentiment analysis, and named entity recognition.

It is designed to be easy to use and accessible to a wide range of users, from business analysts to data scientists.

Some of the key features of Indico include:

  1. Pre-built Models: Indico provides pre-built models for a range of natural language processing tasks, including text classification, sentiment analysis, and named entity recognition.
  2. Custom Models: Indico also allows users to build custom models for their specific use cases, using their own data and domain-specific knowledge.
  3. Interactive Model Training: Indico provides an interactive model training interface that allows users to quickly and easily train custom models, even if they have little or no experience with machine learning.
  4. Easy-to-Use API: Indico provides a simple and intuitive API that makes it easy to use and integrate into existing machine learning workflows.
  5. Security and Compliance: Indico is built with security and compliance in mind, with features such as secure data encryption and SOC 2 Type II certification.
  6. Data Visualization: Indico provides data visualization tools that allow users to explore and analyze their data in a more intuitive way.
  7. Active Community: Indico has an active community of developers and users, with regular updates and new features being added.

Overall, Indico is a powerful and user-friendly NLP platform that provides a range of natural language processing capabilities.

Its pre-built models, custom model training interface, and easy-to-use API make it a popular choice for businesses and data scientists looking to build and train machine learning models for a wide range of NLP tasks.

26

MonkeyLearn

MonkeyLearn is a cloud-based natural language processing (NLP) platform that offers a suite of tools for text analysis and machine learning.

Its core product is a text analysis platform that provides a range of pre-built models for various NLP tasks, such as sentiment analysis, intent classification, entity recognition, and topic extraction. Some key features of MonkeyLearn are:

  • Easy-to-use: MonkeyLearn provides a user-friendly interface for creating and managing text analysis models, with no programming skills required.
  • High accuracy: MonkeyLearn is known for its high accuracy, thanks to its use of machine learning algorithms and deep linguistic analysis.
  • Support for multiple languages: MonkeyLearn supports multiple languages, including English, Spanish, French, German, and Portuguese.
  • Customizable: MonkeyLearn allows users to train their own models using their own data, enabling them to customize the NLP tools to their specific needs.
  • Integration with other tools: MonkeyLearn can be integrated with other tools, such as Zapier, Google Sheets, and Excel, to enhance its functionality and performance.
  • Cloud-based deployment: MonkeyLearn is a cloud-based platform, meaning users can access and use it from anywhere with an internet connection.

MonkeyLearn is widely used in various industries, such as customer service, marketing, and e-commerce. It has found applications in various areas, such as social media monitoring, feedback analysis, and voice-of-customer analysis.

They offer various pricing plans based on the volume of text processed and the types of analysis performed, with a free trial available for testing the product. Additionally, MonkeyLearn provides API access for integration with other applications and programming languages.

27

Wit.ai

Wit.ai is a natural language processing (NLP) platform that allows developers to build conversational interfaces, such as chatbots and voice assistants. It is designed to be easy to use and accessible to developers of all skill levels.

Wit.ai Chatbot

Some of the key features of Wit.ai include:

  1. Intent Recognition: Wit.ai provides powerful intent recognition capabilities, allowing it to understand the meaning behind a user’s message and provide appropriate responses.
  2. Entity Extraction: Wit.ai can extract entities from user messages, such as dates, times, and locations, making it easier to provide relevant responses.
  3. Context Awareness: Wit.ai can understand the context of a conversation, allowing it to provide more personalized and relevant responses.
  4. Natural Language Understanding: Wit.ai uses machine learning algorithms to understand natural language, allowing it to handle complex sentence structures and idiomatic expressions.
  5. Multilingual Support: Wit.ai supports multiple languages, making it a versatile platform for building conversational interfaces for a global audience.
  6. Easy-to-Use API: Wit.ai provides a simple and intuitive API that makes it easy to use and integrate into existing machine learning workflows.
  7. Free Tier: Wit.ai offers a free tier that allows developers to get started with the platform at no cost, making it accessible to developers of all budgets.

Overall, Wit.ai is a powerful and user-friendly NLP platform that provides a range of natural language processing capabilities.

Its intent recognition, entity extraction, and context awareness features make it a popular choice for developers looking to build conversational interfaces, such as chatbots and voice assistants.

28

Jasper Ai Chat

Jasper also an AI Chatbot like ChatGPT, is an AI chatbot developed by Jasper Technologies, a company that specializes in conversational AI. Jasper is designed to help businesses automate their customer service and support functions by providing a conversational interface for their customers.

This is our favorite, ChatGPT alternative due to its templates and quick answers. Jasper is one of the fastest-growing AI content generator tools in 2022.

Here are some of its features of Jasper:

  1. Natural language processing: Jasper uses natural language processing (NLP) to understand the intent behind customer queries and respond in a conversational manner.
  2. Multi-channel support: Jasper can be integrated with a variety of messaging platforms, including web chat, SMS, Facebook Messenger, and more.
  3. Automated responses: Jasper can automate responses to frequently asked questions, reducing the workload for human customer service representatives.
  4. Personalization: Jasper can personalize responses based on customer data and previous interactions.
  5. Intelligent routing: Jasper can intelligently route customer inquiries to the most appropriate human representative based on the nature of the query.
  6. Analytics: Jasper provides detailed analytics on customer interactions, allowing businesses to monitor performance and improve their customer service.
  7. Scalability: Jasper is designed to be highly scalable, allowing businesses to handle a large volume of customer inquiries without adding additional staff.

Overall, Jasper is a powerful tool for businesses looking to streamline their customer service and support functions by leveraging the power of conversational AI. We can say could Be the best Alternative to ChatGPT.

Points To Keep in Mind-

How To Choose A Better AI ChatBot?

Although, we have shared all the best AI Chatbots and free ChatGPT alternatives.

8-must-have-chatbot-features
Image- inbenta.com

But if you’re confused, about how to choose the right AI Chatbot, here we have also shared some details.

  1. Use case: The first and most important factor to consider is the use case of your chatbot. Different chatbots are better suited for different use cases. For example, some chatbots are better suited for customer support, while others are better for lead generation.
  2. Natural language processing (NLP) capabilities: The ability of a chatbot to understand and interpret natural language is critical to its success. Look for a chatbot that has strong NLP capabilities, including the ability to handle complex sentence structures and idiomatic expressions.
  3. Customizability: A good chatbot should be customizable to your brand and your specific use case. Look for a chatbot that allows you to customize its personality, responses, and other aspects to align with your brand.
  4. Integration capabilities: Consider how easily the chatbot can be integrated with your existing systems, such as your CRM or help desk software.
  5. Analytics and reporting: A good chatbot should provide detailed analytics and reporting capabilities, allowing you to track its performance and make data-driven decisions.
  6. Security and compliance: If your chatbot will be handling sensitive information, such as personal or financial data, make sure it meets industry security standards and compliance requirements.
  7. Customer support and documentation: Look for a chatbot provider that offers strong customer support and documentation, including user guides and tutorials, to help you get the most out of your chatbot.

By considering these factors, you can choose an AI chatbot that is better suited for your specific needs and can deliver a better user experience for your customers.

Our Opinion-

Conclusion- Tools & Websites Like ChatGPT 2024

As we have mentioned all the tools that will help you to choose the best alternatives.

When choosing an alternative to ChatGPT, users should carefully consider their specific requirements, evaluate the available options, and select a model that best meets their needs in terms of performance, features, and cost.

At the end of this post, we just want to say that we have mentioned all the details related to OpenAi like ChatGPT that will help you to find out the best option for you.

FAQs-

Queries Related To ChatGPT FREE Alternatives

Here are some potential frequently asked questions (FAQs) that readers may have after reading an article about ChatGPT alternatives:

What is ChatGPT, and why would someone need an alternative?

ChatGPT is a language model that can be used for various natural language processing (NLP) tasks. However, there are several reasons why someone might need an alternative, such as if they need a model that is more specialized for a particular use case, requires better performance, or has a lower cost.

What are some popular Ai like ChatGPT?

There are several popular alternatives to ChatGPT, including BERT, GPT-3, XLNet, and RoBERTa, among others.

How do I choose the right alternative to ChatGPT for my needs?

Choosing the right alternative will depend on your specific requirements, such as the task you need to perform, the amount of data you have available, your budget, and your desired performance. You may need to evaluate several options to determine which one is the best fit for your needs.

Are there any open-source websites like ChatGPT?

Yes, there are several open-source alternatives to ChatGPT, such as Hugging Face’s Transformers, AllenNLP, and OpenAI’s GPT-2.

How does the performance of alternatives to ChatGPT compare to ChatGPT itself?

The performance of alternatives to ChatGPT will vary depending on the specific task and the alternative in question. Some alternatives may perform better than ChatGPT in certain areas, while others may be weaker in certain aspects. It’s important to evaluate each alternative carefully to determine which one is the best fit for your needs.

Are there any downsides to using an alternative like ChatGPT?

Some downsides to using an alternative to ChatGPT may include a steeper learning curve, lower overall performance for certain tasks, and a lack of support or documentation compared to more widely-used models like ChatGPT. It’s important to carefully evaluate the pros and cons of each alternative before making a decision.

Is it possible to use multiple alternatives to ChatGPT for different tasks?

Yes, it’s possible to use multiple alternatives to ChatGPT for different tasks if that is the best approach for your needs. For example, you may use one model for sentiment analysis and another for language translation.

Gaurav Singh Parihar
Gaurav Singh Parihar

Meet Gaurav, the digital marketing enthusiast and Saas Tools expert! With over 3 years of experience at Webmetools, he passionately reviews and creates content around Saas Tools, empowering online businesses to make the right choices for success.

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