Model Description Open source Private
GPT-3 (Top Hugging Face performing model) A 175 billion parameter language model developed by OpenAI. It is capable of generating text, translating languages, writing different kinds of creative content, and answering your questions in an informative way. No Yes
GPT-4 A successor to GPT-3, with 100 trillion parameters. It is still under development, but has shown impressive capabilities in early benchmarks. No Yes
LaMDA A 137 billion parameter language model developed by Google AI. It is focused on dialogue and conversation, and is designed to be more informative and comprehensive than previous language models. No Yes
Jurassic-1 Jumbo A 178 billion parameter language model developed by AI21 Labs. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. No Yes
Megatron-Turing NLG A 530 billion parameter language model developed by Google AI and NVIDIA. It is designed for natural language generation tasks, such as text summarization and translation. No Yes
Wu Dao 2.0 A 1.75 trillion parameter language model developed by Beijing Academy of Artificial Intelligence. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. No Yes
Bloom A 176 billion parameter language model developed by Hugging Face and a consortium of researchers. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. Yes No
PaLM A 540 billion parameter language model developed by Google AI. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. No Yes
Wav2Vec 2.0 Large A 1 billion parameter speech recognition model developed by Facebook AI Research. It is designed to transcribe spoken language into text. Yes No
Bart Large A 137 billion parameter sequence-to-sequence model developed by Facebook AI Research. It is designed for natural language tasks, such as text generation, translation, and question answering. Yes No
T5-XXL A 11 billion parameter sequence-to-sequence model developed by Google AI. It is designed for natural language tasks, such as text summarization, translation, and question answering. Yes No
RoBERTa Large A 137 billion parameter masked language model developed by Facebook AI Research. It is designed for natural language tasks, such as text classification, question answering, and sentiment analysis. Yes No
GPT-Neo 2.7B A 2.7 billion parameter language model developed by EleutherAI. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. Yes No
GPT-NeoX 20B A 20 billion parameter language model developed by EleutherAI. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. Yes No
Falcon A 40 billion parameter language model developed by TII. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. Yes No
LLaMA A 137 billion parameter language model developed by Meta. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. Yes No
Vicuna-13b A 13 billion parameter language model developed by Meta. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. Yes No
MPT-7b-chat A 7 billion parameter language model developed by Mosaic ML. It is designed for chatbot applications. Yes No
Claude v1 A 137 billion parameter language model developed by Anthropic. It is designed for general-purpose language tasks, such as text generation, translation, and question answering. No Yes

Please note that this is not an exhaustive list, and NextAI may support additional models in the future.

Additionally, NextAI offers a variety of tools and features that make it easy to use these models, such as:

This makes NextAI a powerful tool for developers, researchers, and businesses of all sizes.