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. -
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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Databricks
Dolly 2.0
FREEDolly 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. -
Aleph Alpha
Luminous-base
$0.0055Aleph 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
$0.0082Aleph 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
$0.0319Supreme 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
$0.0398Supreme-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. -
Yandex
YaLM
FREEYaLM 100B is a GPT-like neural network for generating and processing text. It can be used freely by developers and researchers from all over the world. It took 65 days to train the model on a cluster of 800 A100 graphics cards and 1.7 TB of online texts, books, and countless other sources in both English and Russian. Researchers and developers can use the corporate-size solution to solve the most complex problems associated with natural language processing.Training details and best practices on acceleration and stabilizations can be found on Medium (English) and Habr (Russian) articles. The model is published under the Apache 2.0 license that permits both research and commercial use.
