Compare Models

  • Deepmind

    Chinchilla AI

    OTHER

    Google’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.

  • StableLM

    StableLM-Base-Alpha -7B

    FREE

    Stability 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.

  • Yandex

    YaLM

    FREE
    YaLM 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.