Compare Models

  • OpenAI

    Ada (fine tuning) GPT-3

    $0.0016
    When fine-tuning a GPT model like Ada, you are fine-tuning the GPT-3 base model (not the instruction-oriented variant of GPT-3). Fine-tuning involves taking the pre-trained base model and further training it on your specific dataset or task to enhance its performance. Fine-tuning allows OpenAI API customers to leverage the power of pre-trained GPT-3 language models, such as Ada, while tailoring them to their specific needs (the fine-tuning process allows a model to specialize in a specific task or context, making it more efficient and effective for a particular use case, which can help to reduce costs and latency for high-volume tasks). You are also able to continue fine-tuning a fine-tuned model to add additional data without having to start from scratch.
    As the smallest GPT-3 model, Ada is less computationally intensive and quicker, making it ideal for tasks that don’t demand complex language understanding or generation. Note: There are two fine-tuning costs to be aware of, a one-time training cost and a pay-as-you-go usage cost.
  • OpenAI

    Ada Instruct model

    $0.004
    Open AI’s Ada is usually the fastest and lowest cost Instruct model. InstructGPT models are sibling models to ChatGPT. They are built on GPT-3 models but made to be safer, more helpful, and more aligned to users’ needs using a technique called reinforcement learning from human feedback (RLHF). Instruct models are meant to generate text with a clear instruction, and they are not optimized for conversational chat. Instruct models are optimized to follow single-turn instructions (e.g., specifically designed to follow instructions provided in a prompt). Developers can use Instruct models for extracting knowledge, generating text, performing NLP tasks, automating tasks involving natural language, and translating languages. The Instruct models also make up facts less often than GPT-3 base models and show slight decreases in toxic output generation. Access is available through a request to OpenAI’s API.

  • OpenAI

    Babbage (fine tuning) GPT-3

    $0.0024
    When fine-tuning a GPT model like Babbage, you are fine-tuning the GPT-3 base model (not the instruction-oriented variant of GPT-3). Fine-tuning involves taking the pre-trained base model and further training it on your specific dataset or task to enhance its performance. Fine-tuning allows OpenAI API customers to leverage the power of pre-trained GPT-3 language models, such as Babbage, while tailoring them to their specific needs (the fine-tuning process allows a model to specialize in a specific task or context, making it more efficient and effective for a particular use case, which can help to reduce costs and latency for high-volume tasks). You are also able to continue fine-tuning a fine-tuned model to add additional data without having to start from scratch.
    Babbage is a medium-sized GPT-3 model. It offers a balance between processing power and computational requirements. It is more capable than Ada but less so than Curie or Davinci. Note: There are two fine-tuning costs to be aware of, a one-time training cost and a pay-as-you-go usage cost.
  • OpenAI

    Babbage Instruct model

    $0.0005

    Open AI’s Babbage Instruct model can understand and generate natural language. Babbage is capable of straightforward tasks, is very fast, and is comparatively lower priced than some other Instruct models. InstructGPT models are sibling models to ChatGPT. They are built on GPT-3 models but made to be safer, more helpful, and more aligned to users’ needs using a technique called reinforcement learning from human feedback (RLHF). Instruct model are meant to generate text with a clear instruction, and they are not optimized for conversational chat. Instruct models are optimized to follow single-turn instructions (e.g., specifically designed to follow instructions provided in a prompt). Developers can use Instruct models for extracting knowledge, generating text, performing NLP tasks, automating tasks involving natural language, and translating languages. Instruct models also make up facts less often than GPT-3 base models and show slight decreases in toxic output generation. Access is available through a request to OpenAI’s API.

  • ChatGLM

    ChatGLM-6B

    FREE
    Researchers at the Tsinghua University in China have worked on developing the ChatGLM series of models that have comparable performance to other models such as GPT-3 and BLOOM. ChatGLM-6B is an open bilingual language model (trained on Chinese and English). It is based on General Language Model (GLM) framework, with 6.2B parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level). The following models are available: ChatGLM-130B (an open source LLM), ChatGLM-100B (not open source but available through invite-only access), and ChatGLM-6 (a lightweight open source alternative). ChatGLM LLMs are available with a Apache-2.0 license that allows commercial use. We have included the link to the Hugging Face page where you can try the ChatGLM-6B Chatbot for free.
  • OpenAI

    ChatGPT (Web Browser Version)

    FREE
    The ChatGPT Web Browser Version is an accessible online powerful language model. The chatbot is designed to provide users with a user-friendly interface that facilitates interaction without needing any specialized programming or machine learning knowledge. Users can leverage ChatGPT for a wide range of applications, including but not limited to tutoring in academic subjects, generating creative content, drafting and editing text, providing personalized recommendations, translating languages, and even programming help. Businesses can use it for automating customer service, generating marketing content, and providing personalized user experiences.
    ChatGPT is powered by GPT-3.5-turbo by default and is free to try. If you are a paying customer and subscribe to ChatGPT Plus, you can change the model to GPT-4 before you start a chat. Currently, the ChatGPT models support several languages, including but not limited to English, Spanish, French, German, Portuguese, Italian and Dutch. New features for ChatGPT-Plus users have just been announced. These include a web-browsing feature that provides up-to-date information (prior to the update, ChatGPT was limited in what it could answer, as it was only trained on data until 2021). ChatGPT-Plus users can also access third-party plug-ins for web services like Expedia, Kayak, and Instacart. With these plug-ins, users can prompt ChatGPT to perform tasks on specific websites.
  • OpenAI

    ChatGPT API

    $0.002
    OpenAI’s ChatGPT API is GPT-3.5-turbo. GPT-3.5-turbo is a more powerful version of GPT-3.5, and it has a larger vocabulary and can generate more realistic and coherent text. The API enables developers to integrate ChatGPT into their applications, products, or services and you can create interactive chatbots and virtual assistants, content generation, writing assistance, language translation, AI tutoring, product recommendations, sentiment analysis, code generation, and email/report drafting. The API is also more suitable for integrating AI into data pipelines, embedding GPT functionality in a dashboard to automatically provide a text summary of the results, and providing a natural language interface to your data. Please note that the ChatGPT API usage cost is not included in the ChatGPT Plus subscription, which is billed separately.
    Currently, the ChatGPT models support several languages, including but not limited to English, Spanish, French, German, Portuguese, Italian and Dutch.
  • Deepmind

    Chinchilla AI

    OTHER

    Google’s DeepMind Chinchilla AI is still in the testing phase. Once released, Chinchilla AI will be useful for developing various artificial intelligence tools, such as chatbots, virtual assistants, and predictive models. It functions in a manner analogous to that of other large language models such as GPT-3 (175B parameters), Jurassic-1 (178B parameters), Gopher (280B parameters), and Megatron-Turing NLG (300B parameters) but because Chinchilla is smaller (70B parameters), inference and fine-tuning costs less, easing the use of these models for smaller companies or universities that may not have the budget or hardware to run larger models.

  • OpenAI

    Curie (fine tuning) GPT-3

    $0.012
    When fine-tuning a GPT model like Curie, you are fine-tuning the GPT-3 base model (not the instruction-oriented variant of GPT-3). Fine-tuning involves taking the pre-trained base model and further training it on your specific dataset or task to enhance its performance. Fine-tuning allows OpenAI API customers to leverage the power of pre-trained GPT-3 language models, such as Curie, while tailoring them to their specific needs (the fine-tuning process allows a model to specialize in a specific task or context, making it more efficient and effective for a particular use case, which can help to reduce costs and latency for high-volume tasks). You are also able to continue fine-tuning a fine-tuned model to add additional data without having to start from scratch.
    Curie is a larger variant of GPT-3, offering more sophisticated language capabilities. It is a good choice for tasks requiring a deeper understanding of context or more complex language generation. Note: There are two fine-tuning costs to be aware of, a one-time training cost and a pay-as-you-go usage cost.
  • OpenAI

    Curie Instruct model

    $0.002

    Open AI’s Instruct model Curie is very capable and is faster and costs less than Davinci. Curie can understand and generate natural language. InstructGPT models are sibling models to ChatGPT. They are built on GPT-3 models but made to be safer, more helpful, and more aligned to users’ needs using a technique called reinforcement learning from human feedback (RLHF). Instruct models are meant to generate text with a clear instruction, and they are not optimized for conversational chat. Instruct models are optimized to follow single-turn instructions (e.g., specifically designed to follow instructions provided in a prompt). Developers can use Instruct models for extracting knowledge, generating text, performing NLP tasks, automating tasks involving natural language, and translating languages. Instruct model also make up facts less often than GPT-3 base models and show slight decreases in toxic output generation. Access is available through a request to OpenAI’s API.

  • OpenAI

    DALL·E 2

    $0.016
    DALL-E 2 is a browser-based AI system that can create realistic images and art from a description in natural language. It currently supports the ability, given a prompt, to create a new image with a certain size, edit an existing image, or create variations of a user-provided image. Currently, DALL·E 2 charges for an image by pixel resolution.
    Also to note, for developers, there is also an API available for the beta version and the API allows you to integrate state of the art image generation capabilities directly into your product. The API usage is offered on a pay-as-you-go basis and is billed separately. To note, OpenAI offers large volume discounts (>$5k/month) through their sale team.

  • OpenAI

    Davinci (fine tuning) GPT-3

    $0.12
    When fine-tuning a GPT model like Davinci, you are fine-tuning the GPT-3 base model (not the instruction-oriented variant of GPT-3). Fine-tuning involves taking the pre-trained base model and further training it on your specific dataset or task to enhance its performance. Fine-tuning allows OpenAI API customers to leverage the power of pre-trained GPT-3 language models, such as Davinci, while tailoring them to their specific needs (the fine-tuning process allows a model to specialize in a specific task or context, making it more efficient and effective for a particular use case, which can help to reduce costs and latency for high-volume tasks). You are also able to continue fine-tuning a fine-tuned model to add additional data without having to start from scratch.
    Davinci is the largest and most powerful variant of GPT-3. It’s the best choice for tasks requiring the most sophisticated language capabilities, but it also requires more processing power and time to generate results. Note: There are two fine-tuning costs to be aware of, a one-time training cost and a pay-as-you-go usage cost.
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