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Compare Models

  • Aleph Alpha

    Luminous-extended

    $0.0082
    Aleph Alpha luminous-extended is the second largest model which is faster and cheaper than Luminous-supreme. the model can perform information extraction, language simplification and has multi-capable image description capability. You can try Aleph Alpha models with predefined examples for free. Go to at the Jumpstart page on their site and click through the examples on Classification and Labelling, Generation, Information Extraction, Translation and Conversion and Multimodal. Aleph Alpha are based in Europe, which allows customers with sensitive data to process their information in compliance with European regulations for data protection and security on a sovereign, European computing infrastructure.
  • Aleph Alpha

    Luminous-supreme

    $0.0319
    Supreme is the largest model but the most expensive Aleph Alpha Luminous model. Supreme can do all the tasks of the other smaller models (it speaks and writes 5 languages, English, French, German, Italian and Spanish and can undertake Information extraction, language simplification, semantically compare texts, summarize documents, perform Q&A tasks and more) and is well suited for creative writing. You can try out the Aleph Alpha models for free. Go to the Jumpstart page on their site and click through the examples on Classification & Labelling, Generation, Information Extraction, Translation & Conversion and Multimodal.
  • Aleph Alpha

    Luminous-supreme-control

    $0.0398
    Supreme-control is its own model, although it is based on Luminous-supreme and is optimized on a certain set of tasks. The models differ in complexity and ability but this model excels when it can be optimized for question and answering and Natural Language Inference.
    You can try out the combination of the Aleph Alpha models with predefined examples for free. Go to at the Jumpstart page on their site and click through the examples on Classification & Labelling, Generation, Information Extraction, Translation & Conversion and Multimodal.

  • Microsoft, NVIDIA

    MT-NLG

    OTHER
    MT-NLG (Megatron-Turing Natural Language Generation) uses the architecture of the transformer-based Megatron to generate coherent and contextually relevant text for a range of tasks, including completion prediction, reading comprehension, commonsense reasoning, natural language inferences, and word sense disambiguation. MT-NLG is the successor to Microsoft Turing NLG 17B and NVIDIA Megatron-LM 8.3B. The MT-NLG model is three times larger than GPT-3 (530B vs 175B). Following the original Megatron work, NVIDIA and Microsoft trained the model on over 4,000 GPUs. NVIDIA has announced an Early Access program for its managed API service to the MT-NLG model for organizations and researchers.
  • 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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