Compare Models
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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. -
ChatGLM
ChatGLM-6B
FREEResearchers at the Tsinghua University in China have worked on developing the ChatGLM series of models that have comparable performance to other models such as GPT-3 and BLOOM. ChatGLM-6B is an open bilingual language model (trained on Chinese and English). It is based on General Language Model (GLM) framework, with 6.2B parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level). The following models are available: ChatGLM-130B (an open source LLM), ChatGLM-100B (not open source but available through invite-only access), and ChatGLM-6 (a lightweight open source alternative). ChatGLM LLMs are available with a Apache-2.0 license that allows commercial use. We have included the link to the Hugging Face page where you can try the ChatGLM-6B Chatbot for free. -
Deepmind
Chinchilla AI
OTHERGoogle’s DeepMind Chinchilla AI is still in the testing phase. Once released, Chinchilla AI will be useful for developing various artificial intelligence tools, such as chatbots, virtual assistants, and predictive models. It functions in a manner analogous to that of other large language models such as GPT-3 (175B parameters), Jurassic-1 (178B parameters), Gopher (280B parameters), and Megatron-Turing NLG (300B parameters) but because Chinchilla is smaller (70B parameters), inference and fine-tuning costs less, easing the use of these models for smaller companies or universities that may not have the budget or hardware to run larger models.
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Technology Innovation Institute
Falcon-40B
OTHERThe Technology Innovation Institute (TII), an Abu Dhabi government funded research institution, has introduced Falcon, a state-of-the-art autoregressive decoder-only language model series released under the Apache 2.0 license, which means it can be used for commerical and research uses.
The family includes Falcon-40B and Falcon-7B, trained on 1 trillion tokens, mainly (>80%) from the RefinedWeb datase. A special variant, Falcon-40B-Instruct, has been made available which may be more suitable for assistant-style tasks. Falcon-40B can support English, German, Spanish, French (and limited capabilities in Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish). It can be used to generate creative text and solve complex problems, chatbots, virtual assistants, language translation, content generation, and sentiment analysis (and more).To use these models, PyTorch 2.0 is required. TII is now calling for proposals from users worldwide to submit their most creative ideas for Falcon 40B’s deployment – https://falconllm.tii.ae/call-for-proposal.php or you can pay to access it via Amazon SageMaker JumpStart.
A demo of Falcon-Chat is available on Hugging Face at https://huggingface.co/spaces/HuggingFaceH4/falcon-chat. -
Technology Innovation Institute
Falcon-7B
FREEThe Technology Innovation Institute (TII), an Abu Dhabi government funded research institution, has introduced Falcon, a state-of-the-art autoregressive decoder-only language model series released under the Apache 2.0 license, which means it can be used for commerical and research uses. Falcon-7B only needs ~15GB and therefore is accessible even on consumer hardware. The model can support English, German, Spanish, French (and limited capabilities in Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish). It can be used to generate creative text and solve complex problems, chatbots, customer service operations, virtual assistants, language translation, content generation, and sentiment analysis.
This raw pretrained model should be finetuned for specific use cases. Falcon-7B-Instruct is also available at https://huggingface.co/tiiuae/falcon-7b-instruct.
If you are looking for a version better-suited model to take generic instructions in a chat format, we recommend Falcon-7B-Instruct rather than the base model. -
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. -
Amazon
SageMaker
FREEAmazon SageMaker enables developers to create, train, and deploy machine-learning (ML) models in the cloud. SageMaker also enables developers to deploy ML models on embedded systems and edge-devices. Amazon SageMaker JumpStart helps you quickly and easily get started with machine learning. The solutions are fully customizable and supports one-click deployment and fine-tuning of more than 150 popular open source models such as natural language processing, object detection, and image classification models that can help with extracting and analyzing data, fraud detection, churn prediction and personalized recommendations.The Hugging Face LLM Inference DLCs on Amazon SageMaker, allows support the following models: BLOOM / BLOOMZ, MT0-XXL, Galactica, SantaCoder, GPT-Neox 20B (joi, pythia, lotus, rosey, chip, RedPajama, open assistant, FLAN-T5-XXL (T5-11B), Llama (vicuna, alpaca, koala), Starcoder / SantaCoder, and Falcon 7B / Falcon 40B. Hugging Face’s LLM DLC is a new purpose-built Inference Container to easily deploy LLMs in a secure and managed environment. -
StableLM
StableLM-Base-Alpha -7B
FREEStability AI released a new open-source language model, StableLM. The Alpha version of the model is available in 3 billion and 7 billion parameters. StableLM is trained on a new experimental dataset built on The Pile, but three times larger with 1.5 trillion tokens of content. The richness of this dataset gives StableLM surprisingly high performance in conversational and coding tasks, despite its small size. The models are now available on GitHub and on Hugging Face, and developers can freely inspect, use, and adapt our StableLM base models for commercial or research purposes subject to the terms of the CC BY-SA-4.0 license.
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Cohere
Summarize
$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 and is available as an API that can be integrated into various libraries using Python, Node, or Go software development kits (SDKs).Cohere Summarize generates a succinct version of a provided text. This summary relays the most important messages of the text, and a user can configure the results with a variety of parameters to support unique use cases. It can instantly encapsulate the key points of a document and provides text summarization capabilities at scale. -
LMSYS Org
Vicuna-13B
FREEVicuna-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.
