  We present SynthCLIP, a CLIP model trained on entirely synthetic text-image
pairs. Leveraging recent text-to-image (TTI) networks and large language models
(LLM), we generate synthetic datasets of images and corresponding captions at
scale, with no human intervention. In this work, we provide an analysis on CLIP
models trained on synthetic data. We provide insights on the data generation
strategy, number of samples required, scaling trends, and resulting properties.
We also introduce SynthCI-30M, a purely synthetic dataset comprising 30 million
captioned images. Our code, trained models, and data, are released as open
source at https://github.com/hammoudhasan/SynthCLIP
