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Compare Models

  • Google

    Flan-UL2

    FREE
    Developed by Google, Flan-UL2, which is a more powerful version of the T5 model that has been trained using Flan, and it is downloadable from Hugging Face. It shows performance exceeding the ‘prior’ versions of Flan-T5. With the ability to reason for itself and generalize better than the previous models, Flan-UL2 is a great improvement. Flan-UL2 is a machine learning model that can generate textual descriptions of images and has the potential to be used for image search, video captioning, automated content generation, and visual question answering. Flan-UL2 has an Apache-2.0 license, which is a permissive open source license that allows for commercial use.
    If Flan-UL2’s 20B parameters are too much, consider the previous iteration of Flan-T5, which comes in five different sizes and might be more suitable for your needs.
  • OpenAI

    GPT-3.5-turbo 16k

    $0.004
    GPT-3.5-turbo 16k has the same capabilities as the standard gpt-3.5-turbo (4k model) but with 4 times the context but at twice the price. In general, a larger context window can be more powerful because it takes into account more information from the surrounding text, which can lead to better predictions
    GPT-3.5-turbo was designed to provide better performance and is well-known as the model that, by default, powers ChatGPT. However, paying customers who subscribe to ChatGPT Plus can change the model to GPT-4 before you start a chat.
    GPT-3.5-turbo is optimized for conversational formats and is superior to GPT-3 models, and the performance of GPT-3.5-turbo is on par with Instruct Davinci-003. GPT-3.5-turbo was trained on a massive corpus of text data, including books, articles, and web pages from across the internet and is used for tasks like content and code generation, question answering, translation, and more. Access is available through a request to OpenAI’s API or through the web application (try for free).
  • OpenAI

    GPT-3.5-turbo 4k

    $0.002
    GPT-3.5-turbo is an upgraded version of the GPT-3 model. It was designed to provide better performance and is well-known as the model that, by default, powers ChatGPT (however, paying customer who subscribe to ChatGPT Plus can change the model to GPT-4 before you start a chat).
    GPT-3.5-turbo is optimized for conversational formats and is superior to GPT-3 models, and the performance of GPT-3.5-turbo is on par with Instruct Davinci-003 (however is also ten times cheaper and has been seen to be three times faster). GPT-3.5-turbo was trained on a massive corpus of text data, including books, articles, and web pages from across the internet and is used for tasks like content and code generation, question answering, translation, and more. In some cases, GPT-3.5-turbo results can sometimes be too “chatty” or “creative”. Access is available through a request to OpenAI’s API or through the web application (try for free).

  • OpenAI

    GPT-4 32K context

    $0.12

    GPT-4 is OpenAI’s new design that incorporates additional improvements and advancements, including being multimodal so it can take both text and image inputs. With broad general knowledge and domain expertise, GPT-4 can follow complex instructions in natural language and solve difficult problems with accuracy. GPT-4 has a more diverse range of training data, incorporating additional languages and sources beyond just English. This means that the model will be able to process and generate text in multiple languages and better understand the nuances and subtleties of different languages and dialects. This is the extended 32k token context-length model, which is separate to the 8k model (and is more expensive).

    GPT-4 API access is now available.

     

    Note: At the time of writing, ChatGPT Plus subscribers can access Chat GPT-4 by logging into the web application.

  • OpenAI

    GPT-4 8K context

    $0.06

    GPT-4 is OpenAI’s new design that incorporates additional improvements and advancements, including being multimodal so it can take both text and image inputs. With broad general knowledge and domain expertise, GPT-4 can follow complex instructions in natural language and solve difficult problems with accuracy. GPT-4 has a more diverse range of training data, incorporating additional languages and sources beyond just English. This means that the model will be able to process and generate text in multiple languages and better understand the nuances and subtleties of different languages and dialects. There are a few different GPT-4 models to choose from. The standard GPT-4 model offers 8k tokens for the context. GPT-4 API access is now available.

    Note: For the ChatGPT web application, ChatGPT is powered by GPT-3.5 turbo by default. However, if you are a paying customer and subscribe to ChatGPT Plus, you can change the model to GPT-4 before you start a chat.

  • Google

    LaMDA

    OTHER
    LaMDA stands for Language Model for Dialogue Application. It is a conversational Large Language Model (LLM) built by Google as an underlying technology to power dialogue-based applications that can generate natural-sounding human language. LaMDA is built by fine-tuning a family of Transformer-based neural language models specialized for dialog and teaching the models to leverage external knowledge sources. The potential use cases for LaMDA are diverse, ranging from customer service and chatbots to personal assistants and beyond. LaMDA is not open source; currently, there are no APIs or downloads. However, Google is working on making LaMDA more accessible to researchers and developers. In the future, it is likely that LaMDA will be released as an open source project, and that APIs and downloads will be made available.
  • Google

    PaLM 2 chat-bison-001

    $0.0021535
    PaLM 2 has just launched (May 2023) and is Google’s next-generation Large Language Model, built on Google’s Pathways AI architecture. PaLM 2 was trained on a massive dataset of text and code, and it can handle many different tasks and learn new ones quickly. It is seen as a direct competitor to OpenAI’s GPT-4 model. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency (100 languages), and natural language generation better than our previous state-of-the-art LLMs, including its predecessor PaLM.
    PaLM 2 is the underlying model driving the PaLM API that can be accessed through Google’s Generative AI Studio. PaLM 2 has four submodels with different sizes. Bison is the best value in terms of capability and chat-bison-001 has been fine-tuned for multi-turn conversation use cases. If you want to see PaLM 2 capabilities, the simplest way to use it is through Google Bard (PaLM 2 is the technology that powers Google Bard).

     

    Watch Paige Bailey introducing PaLM 2: view here

  • ChatGLM

    PaLM 2 text-bison-001

    $0.004
    PaLM 2 has just launched (May 2023) and is Google’s next-generation Large Language Model, built on Google’s Pathways AI architecture. PaLM 2 was trained on a massive dataset of text and code, and it can handle many different tasks and learn new ones quickly. It is seen as a direct competitor to OpenAI’s GPT-4 model. It excels at advanced reasoning tasks, including code and math, classification, question answering, translation and multilingual proficiency (100 languages), and natural language generation better than our previous state-of-the-art LLMs, including its predecessor PaLM.

     

    PaLM 2 is the underlying model driving the PaLM API that can be accessed through Google’s Generative AI Studio. PaLM 2 has four submodels with different sizes. Bison is the best value in terms of capability and cost, and text-bison-001 can be fine-tuned to follow natural language instructions and is suitable for various language tasks such as classification, sentiment analysis, entity extraction, extractive question answering, summarization, re-writing text in a different style, and concept ideation.

     

    If you want to see PaLM 2 capabilities, the simplest way to use it is through Google Bard (PaLM 2 is the technology that powers Google Bard).

     

    Watch Paige Bailey introducing PaLM 2: view here

  • Google

    PaLM 2 textembedding-gecko-001

    $0.0004
    PaLM 2 has just launched (May 2023) and is Google’s next-generation Large Language Model, built on Google’s Pathways AI architecture. PaLM 2 was trained on a massive dataset of text and code, and it can handle many different tasks and learn new ones quickly. It is seen as a direct competitor to OpenAI’s GPT-4 model. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency (100 languages), and natural language generation better than our previous state-of-the-art LLMs, including its predecessor PaLM.
    PaLM 2 is the underlying model driving the PaLM API that can be accessed through Google’s Generative AI Studio. PaLM 2 has four submodels with different sizes: Unicorn (the largest), Bison, Otter, and Gecko (the smallest) and the different sizes of the submodels allow PaLM 2 to be more efficient and to perform different tasks. Gecko is the smallest and cheapest model for simple tasks and textembedding-gecko-001 returns model embeddings for text inputs.
    If you want to see PaLM 2 capabilities, the simplest way to use it is through Google Bard (PaLM 2 is the technology that powers Google Bard).

     

    Watch Paige Bailey introducing PaLM 2: view here

  • OpenAI

    text-davinci-003

    $0.02
    Text-davinci-003 is recognized as GPT 3.5 and is a variant of the GPT-3 model. While both Davinci and text-davinci-003 are powerful models, they differ in a few key ways. Text-davinci-003 is a newer and more capable model explicitly designed for instruction-following tasks. Text-davinci-003 was trained on a more recent dataset containing data up to June 2021. It can do any language task with better quality, longer output, and consistent instruction-following than the Curie, Babbage, or Ada models. Text-davinci-003 supports a longer context window (max prompt plus completion length) than Davinci.
    For those requesting the OpenAI’s API, GPT-3.5-turbo may be a better choice for tasks that require high accuracy in math or zero-shot classification and sentiment analysis than text-davinci-003. To note, GPT-3.5-turbo performs at a similar capability to text-davinci-003 but at 10 percent the price per token. OpenAI recommends GPT-3.5-turbo for most use cases.

  • OpenAI

    text-embedding-ada-002

    $0.0001
    An embedding API model, such as Ada, is a powerful tool that converts words into numerical representations, enabling computers to understand and process natural language more effectively. This process is crucial for developing machine learning algorithms and artificial intelligence systems that can interact with humans, analyze text, or make predictions based on text. OpenAI’s text embeddings is built for advanced search, clustering, topic modeling, and classification functionality.
    Access is available through a request to OpenAI’s API.

  • OpenAI

    Whisper

    0.006

    Whisper is an automatic speech recognition (ASR) system capable of transcribing in multiple languages as well as translating them into English. With Whisper, you can easily transcribe speech into text, allowing you to capture conversations and meetings for future reference. And if you need to communicate with someone who speaks a different language, Whisper can help with that too — it can translate many different languages into English, making it easier than ever to bridge the gap and ensure that everyone is on the same page.

    Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. The speech to text API has two endpoints (transcriptions and translations) and file uploads are currently limited to 25 MB, and the following input file types are supported: mp3, mp4, mpeg, mpga, m4a, wav, and webm.
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Ada (fine tuning) GPT-3
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