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GPT4All vs. Phi

LLM Comparison


GPT4All

GPT4All

Overview

Describing itself as an ecosystem for open-source chatbots, Nomic provides a framework for training LLMs with LLaMA and GPT-J backbones.



Initial release: 2023-03-26

Further Reading

Phi

Phi

Overview

Phi is a series of compact language models developed by Microsoft using textbooks and synthetic data.


Phi-1 and Phi-2 are 1.3B and 2.7B parameter language models, respectively, developed by Microsoft to demonstrate the ability of smaller language models trained on high-quality data. Despite its size and not having an instruct finetuned counterpart, the Phi-2 model is well-suited to research and experimentation given its size and MIT license.


Initial release: 2023-06-20

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More Comparisons

GPT4All

Phi
Products & Features
Instruct Models
Coding Capability
Customization
Finetuning
Open Source
License Varies MIT
Model Sizes 7B, 13B 1.3B, 2.7B

Other GPT4All Comparisons

GPT4All vs. Alpaca GPT4All vs. Cerebras-GPT GPT4All vs. Dolly GPT4All vs. Falcon GPT4All vs. FastChat GPT4All vs. FLAN-T5 GPT4All vs. FLAN-UL2 GPT4All vs. Gemma GPT4All vs. Gemma 2 GPT4All vs. GPT-J GPT4All vs. GPTNeo GPT4All vs. Grok GPT4All vs. Guanaco GPT4All vs. Koala GPT4All vs. LLaMA GPT4All vs. Llama 2 GPT4All vs. Llama 3 GPT4All vs. Mistral GPT4All vs. MPT GPT4All vs. OpenAssistant GPT4All vs. OpenLLaMA GPT4All vs. OPT GPT4All vs. Orca GPT4All vs. Phi GPT4All vs. Pythia GPT4All vs. RedPajama-INCITE GPT4All vs. StableLM GPT4All vs. StableVicuna GPT4All vs. Vicuna GPT4All vs. WizardLM

Other Phi Comparisons

Phi vs. Alpaca Phi vs. Cerebras-GPT Phi vs. Dolly Phi vs. Falcon Phi vs. FastChat Phi vs. FLAN-T5 Phi vs. FLAN-UL2 Phi vs. Gemma Phi vs. Gemma 2 Phi vs. GPT-J Phi vs. GPT4All Phi vs. GPTNeo Phi vs. Grok Phi vs. Guanaco Phi vs. Koala Phi vs. LLaMA Phi vs. Llama 2 Phi vs. Llama 3 Phi vs. Mistral Phi vs. MPT Phi vs. OpenAssistant Phi vs. OpenLLaMA Phi vs. OPT Phi vs. Orca Phi vs. Pythia Phi vs. RedPajama-INCITE Phi vs. StableLM Phi vs. StableVicuna Phi vs. Vicuna Phi vs. WizardLM

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