Compare Models
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Stanford University
Alpaca
FREEStanford University released an instruction-following language model called Alpaca, which was fine-tuned from Meta’s LLaMA 7B model. The Alpaca model was trained on 52K instruction-following demonstrations generated in the style of self-instruct using text-davinci-003. Alpaca aims to help the academic community engage with the models by providing an open source model that rivals OpenAI’s GPT-3.5 (text-davinci-003) models. To this end, Alpaca has been kept small and cheap (fine-tuning Alpaca took 3 hours on 8x A100s which is less than $100 of cost) to reproduce. All training data and techniques have been released. The Alpaca license explicitly prohibits commercial use, and the model can only be used for research/personal projects, and users need to follow LLaMA’s license agreement. -
BigScience
BLOOM
FREEBigScience 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. -
BloombergGPT
BloombergGPT
OTHERBloombergGPT represents the first step in developing and applying LLM and generative AI technology for the financial industry. Bloomberg GPT has been trained on enormous amounts of financial data and is purpose-built for finance. The mixed dataset training leads to a model that outperforms existing LLMs on financial tasks by significant margins without sacrificing performance on general LLM benchmarks. Bloomberg GPT can perform a range of NLP tasks such as sentiment analysis, named entity recognition, news classification, and even writing headlines. With Bloomberg GPT, traders and analysts can perform financial analysis and insights more quickly and efficiently, saving valuable time that can be used for other critical tasks. To use Bloomberg GPT, you need access to Bloomberg’s terminal software (a platform investors and financial professionals use to access real-time market data, breaking news, financial research, and advanced analytics). Bloomberg also offers a variety of other subscription options, including subscriptions for financial institutions, universities, and governments. The price of a Bloomberg terminal varies depending on the type of subscription and the number of users. -
Cohere
Generate
$0.015Cohere is a Canadian startup that provides high-performance and secure LLMs for the enterprise. Their models work on public, private, or hybrid clouds.Cohere Generate can be used for tasks such as copywriting, named entity recognition, paraphrasing, and summarization. It can be particularly useful for automating time-consuming and repetitive copywriting tasks and re-wording text to suit a specific reader or context.Cohere Generate is available as an API that can be integrated into various libraries using Python, Node, or Go software development kits (SDKs).We have shown the price of the Cohere Generate Default version, but a Cohere Generate Custom model is available but is double the price (0.030 per 1/k tokens). However, custom models can lead to some of the best-performing NLP models for many tasks. -
EleutherAI
GPT-J
FREEEleutherAI is a leading non-profit research institute focused on large-scale artificial intelligence research. EleutherAI has trained and released several LLMs and the codebases used to train them. GPT-J can be used for code generation, making a chat bot, story writing, language translation and searching. GPT-J learns an inner representation of the English language that can be used to extract features useful for downstream tasks. The model is best at what it was pretrained for, which is generating text from a prompt. EleutherAI has a web page where you can test to see how the GPT-J works, or you can run GPT-J on google colab, or use the Hugging Face Transformers library. -
EleutherAI
GPT-NeoX-20B
FREEEleutherAI has trained and released several LLMs and the codebases used to train them. EleutherAI is a leading non-profit research institute focused on large-scale artificial intelligence research. GPT-NeoX-20B is a 20 billion parameter autoregressive language model trained on the Pile using the GPT-NeoX library. Its architecture intentionally resembles that of GPT-3, and is almost identical to that of GPT-J- 6B. Its training dataset contains a multitude of English-language texts, reflecting the general-purpose nature of this model. It is a transformer-based language model and is English-language only, and thus cannot be used for translation or generating text in other languages. It is freely and openly available to the public through a permissive license. -
AI21 Labs
Jurassic-2 Grande (Base & Instruct)
$0.01J2-Grande offers enhanced text generation capabilities, making it well-suited to language tasks with a greater degree of complexity. Its fine-tuning options allow for optimization of quality, while maintaining an affordable price and high efficiency (see site for more details). It is an ideal choice for complex language processing tasks and generative text applications. All of J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage. -
AI21 Labs
Jurassic-2 Jumbo (Base & Instruct)
$0.015As the largest and most powerful model in the Jurassic series, J2-Jumbo is an ideal choice for the most complex language processing tasks and generative text applications. Further, the model can be fine-tuned for optimum performance in any custom application. Jurassic-2 not only improves upon Jurassic-1 (AI21 Studio previous generation models) in every aspect, making it highly versatile in general purpose text-generators, and capable of composing human-like text and solving complex tasks such as question answering and text classification. All of the J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage. -
AI21 Labs
Jurassic-2 Large (Base & Instruct)
$0.003Designed for fast responses, the Jurassic-2 Large model can be fine-tuned to optimize performance for relatively simple tasks, making it an ideal choice for language processing tasks that require maximum affordability and less processing power. All of the J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage.
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NVIDIA
LaunchPad
FREENVIDIA 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
FREEMeta 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
FREEMeta 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
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