GPT-Neo is the code name for a series of transformer-based language models loosely styled around the GPT architecture that we plan to train and open source. Our primary goal is to replicate a GPT-3 sized model and open source it to the public, for free.

Along the way we will be running experiments with alternative architectures and attention types, releasing any intermediate models, and writing up any findings on our blog.

Our models are built in Tensorflow-mesh, which will allow us to scale up to GPT-3 sizes and beyond using simultaneous model and data parallelism.


  • We have the bulk of the model built, GPT-2 size models trained, and several experimental architectures implemented.

  • Our current codebase should be able to scale up to GPT-3 sized models

Next Steps:

  • We are currently working on wrapping up GPT-2-sized model replication, looking mostly at evaluations there.

  • The largest model we've gotten to train for a single step so far has been 200B parameters.