NEW WEBSITE LAUNCH
Subscribe to our newsletter

Compare Models

  • 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.
  • Meta AI

    Llama

    FREE
    Meta has created Llama (Large Language Model Meta AI), its state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI. Smaller, more performant models such as LLaMA enable others in the research community who don’t have access to large amounts of infrastructure to study these models, further democratizing access in this important, fast-changing field.
    Training smaller foundation models like Llama is desirable in the Large Language Model space because it requires far less computing power and resources to test new approaches, validate others’ work, and explore new use cases. Foundation models train on a large set of unlabeled data, which makes them ideal for fine-tuning for a variety of tasks. Meta is making Llama available at several sizes (7B, 13B, 33B, and 65B parameters) and they also share a Llama model card that details how we built the model in keeping with our approach to responsible AI practices.

  • Meta AI

    Llama 2

    FREE
    Meta has released Llama 2. It has an open license, which allows commercial use for businesses. Llama 2 will be available for use in the Hugging Face Transformers library from today (you will need to sign Meta’s Llama 2 Community License Agreement – https://ai.meta.com/resources/models-and-libraries/llama-downloads/, via MSFT Azure cloud computing service, and through Amazon SageMaker JumpStart).
    Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. Llama 2 is intended for commercial and research use in English. It comes in a range of parameter sizes—7 billion, 13 billion, and 70 billion—as well as pre-trained and fine-tuned variations. According to Meta, the tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align to human preferences for helpfulness and safety. Llama 2 was pre-trained on 2 trillion tokens of data from publicly available sources. The tuned models are intended for assistant-like chat, whereas pre-trained models can be adapted for a variety of natural language generation tasks.
    Link to the live demo of Llama2 70B Chatbot -https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI

  • Aleph Alpha

    Luminous-base

    $0.0055
    Aleph Alpha have the Luminous large language model. Luminous models vary in size, price and parameters. Luminous-base speaks and writes 5 languages: English, French, German, Italian and Spanish and the model can perform information extraction, language simplification and has multi-capable image description capability. Aleph Alpha is targeting “critical enterprises” — organizations like law firms, healthcare providers and banks, which rely heavily on trustable, accurate information. You can try Aleph Alpha models for free. Go to the Jumpstart page on their site and click through the examples on Classification and Labelling, Generation, Information Extraction, Translation & Conversion and Multimodal. Aleph Alpha are based in Europe, allowing 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-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.

  • 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

  • LMSYS Org

    Vicuna-13B

    FREE

    Vicuna-13B is an open-source chatbot developed by a team of researchers from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego. The chatbot was trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. There is a 13B and 7B parameter models that are available on Hugging Face.

    Vicuna-13B achieves more than 90% quality of OpenAI ChatGPT and Google Bard while outperforming other models like LLaMA and Stanford Alpaca in more than 90% of cases. The code and weights and an online demo are publicly available for non-commercial use. Here is a link to learn more about how it compares to other models – https://lmsys.org/blog/2023-03-30-vicuna/.

    To use this model, you need to install LLaMA weights first and convert them into Hugging Face weights, and the cost of training Vicuna-13B is around $300.

1 2

BARD
This website uses cookies to improve your experience. By using this website you agree to our Privacy Policy Policy.