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Compare Models

  • BigScience

    BLOOM

    FREE
    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) is a transformer-based LLM. Over 1,000 AI researchers created it to provide a free large language model for everyone who wants to try and it is a multilingual LLM. BLOOM is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. It can output coherent text in 46 languages and 13 programming languages. It is free, and everybody who wants to can try it out. To interact with the API, you’ll need to request a token. This is done with a post request to the server. Tokens are only valid for two weeks. After which, a new one must be generated. Trained on around 176B parameters, it is considered an alternative to OpenAI models. There is a downloadable model, and a hosted API is available.

  • Databricks

    Dolly 2.0

    FREE
    Dolly 2.0 by Databricks, is the first open source, instruction-following Large Language Model, fine-tuned on a human-generated instruction dataset and is licensed for research and commercial use, which means any organization can create, own, and customize powerful LLMs that can talk to people without paying for API access or sharing data with third parties.

    Dolly 2.0 is a 12B parameter language model based on the EleutherAI pythia model family and fine-tuned exclusively on a new, high-quality human generated instruction following dataset (crowdsourced among Databricks employees – so cool). Dolly-v2-12b is not a state-of-the-art model, but it does exhibit surprisingly high-quality instruction following behavior not characteristic of the foundation model on which it is based. Dolly v2 is also available in smaller model sizes: dolly-v2-7b, a 6.9 billion parameter based on pythia-6.9b and dolly-v2-3b, a 2.8 billion parameter based on pythia-2.8b.

    Dolly 2.0 can be used for brainstorming, classification, open Q&A, closed Q&A, content generation, information extraction, and summarization. You can access the Dolly 2.0 can training code, the dataset, and the model weights on Hugging Face.
  • NVIDIA

    LaunchPad

    FREE
    NVIDIA LaunchPad provides free access to enterprise NVIDIA hardware and software through an internet browser. NVIDIA customers can experience the power of AI with end-to-end solutions through guided hands-on labs or use NVIDIA-Certified Systems as a sandbox, but you need to fill out an Application Form and wait for approval. Sample labs include training and deploying a support chatbot, deploying an end-to-end AI workload, configuring and deploying a language model on the hardware accelerator, and deploying a fraud detection model.

     

    *FREE via Application Form
  • 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.

  • 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.
  • NVIDIA

    NeMo

    FREE
    NVIDIA NeMo, part of the NVIDIA AI platform, is an end-to-end, cloud-native enterprise framework to help build, customize, and deploy generative AI models. NeMo makes generative AI model development easy, cost-effective and fast for enterprises. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. NeMo framework supports both language and image generative AI models. Currently, the workflow for language is in open beta, and the workflow for images is in early access. You must be a member of the NVIDIA Developer Program and logged in with your organization’s email address to access it. It is licensed under the Apache License 2.0, which is a permissive open source license that allows for commercial use.
  • 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.

BLOOM
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