{"id":844,"date":"2023-09-23T11:50:27","date_gmt":"2023-09-23T11:50:27","guid":{"rendered":"https:\/\/tbekk.com\/devstream\/?p=844"},"modified":"2023-09-23T11:54:17","modified_gmt":"2023-09-23T11:54:17","slug":"top-5-free-alternatives-to-gpt-4","status":"publish","type":"post","link":"https:\/\/tbekk.com\/devstream\/2023\/09\/23\/top-5-free-alternatives-to-gpt-4\/","title":{"rendered":"Top 5 Free Alternatives to GPT-4"},"content":{"rendered":"\n

Think GPT-4 is a big deal? These Generative AI newbies are already stealing the show!<\/em><\/h2>\n\n\n\n

LlaMA 2<\/h1>\n\n\n\n

LlaMA 2<\/a> is a family of state-of-the-art open-source large language models released by Meta AI. You can use it for commercial use, and it comes with the code, pre-trained models, and fine-tuned models. All of the resources are available at HuggingFace, and you can even experience the model performance by trying it out on HuggingChat<\/a>. By making Llama 2 openly available, Meta AI is enabling researchers and developers to build innovative applications powered by advanced language capabilities.\"Top
Image from HuggingChat<\/a><\/p>\n\n\n\n

Claude 2<\/h1>\n\n\n\n

Claude 2<\/a> is the latest iteration of Anthropic’s conversational AI assistant. It has improved performance, longer responses, and can be accessed via API as well as a new public-facing beta website, claude.ai. The developers at Anthropic have focused on enhancing its abilities in areas like coding, math, and logical reasoning compared to previous Claude versions. For example, Claude2 recently scored 76.5% on the multiple-choice section of the Bar exam, a significant jump up from 73.0% for Claude 1.3.<\/p>\n\n\n\n

You can access all types of Claude models on Poe<\/a> and experience the performance yourself. \"Top
Image from Poe<\/a><\/p>\n\n\n\n

PaLM 2<\/h1>\n\n\n\n

Google AI PaLM 2<\/a> is Google’s latest large language model that excels at advanced reasoning tasks, including code, math, classification, question answering, translation, multilingual proficiency, and natural language generation. It outperforms previous state-of-the-art large language models like the original PaLM across all these capabilities due to its optimized compute-scaling approach, enhanced dataset mixture, and architectural improvements.<\/p>\n\n\n\n

You can access it for free using Bard<\/a>. <\/p>\n\n\n\n

There is an enchantment, but it is still far away from GPT-4 quality and performance. \"Top
Image from Bard<\/a><\/p>\n\n\n\n

Vicuna 1.3<\/h1>\n\n\n\n

Vicuna-33b-v1.3<\/a> was fine-tuned from LLaMA with supervised instruction fine-tuning on 125K conversations collected from ShareGPT.com<\/a>. It is one of many top performing models on Open LLM Leaderboard<\/a>. You can access the model for free on HuggingFace or try the official demo on lmsys.org<\/a>.\"Top
Image from lmsys.org<\/a><\/p>\n\n\n\n

MPT-30B-Chat<\/h1>\n\n\n\n

MPT-30B-Chat<\/a> is a chatbot that was fine tuned to generate the dialogues. It was created by fine tuning the MPT 30B on multiple dialogue datasets ( ShareGPT-Vicuna, Camel-AI, GPTeacher, Guanaco, Baize and some generated datasets). MPT-30B-Chat is one of the top model on Open LLM leaderboard and you can experience it for free on a Hugging Face Space by mosaicml<\/a>.\"Top
Image from MPT-30B-Chat<\/a><\/p>\n\n\n\n

Conclusion<\/h1>\n\n\n\n

While GPT-4 remains closed and inaccessible, exciting open-source large language models are emerging as alternatives that anyone can use. Models like Anthropic’s Claude2, Meta’s LLaMA2, and MPT-30B show remarkable progress in conversational ability, reasoning, and multilingual versatility. Although not as massive in scale as GPT-4, these freely available models demonstrate that state-of-the-art language AI continues to advance rapidly. Their strengths in areas like math, coding, and logic make them capable replacements for many applications.<\/p>\n\n\n\n

After the launch of LlaMA2 models, there has been a boom of high-performing models that are fine-tuned on various datasets. You can check all of them on the\u00a0Open LLM Leaderboard<\/a>.<\/p>\n\n\n\n

\n\n\n\n