Open Source

Four years into Zen’s development, it’s worth stepping back to assess where we are and where we’re going. Open AI development has made remarkable progress. It also faces significant challenges. Here’s my honest assessment. What We’ve Achieved Competitive Models Open models now match or exceed proprietary alternatives in many domains: Coding: Open models lead on HumanEval and MBPP Reasoning: Competitive on GSM8K and MATH General knowledge: Within 5% on MMLU Multilingual: Often superior for non-English languages The capability gap that seemed insurmountable in 2021 has largely closed for models under 100B parameters....

Training large language models requires more than algorithms. It requires infrastructure: distributed training frameworks, data pipelines, experiment tracking, and evaluation harnesses. Today we open source Training Gym, our complete platform for model development. Why Training Gym? Open AI development faces an infrastructure gap. Publishing model weights is valuable, but it’s not enough. Researchers need: Reproducible training pipelines Scalable distributed training Standardized evaluation Experiment management Data processing tools Training Gym provides all of this in an integrated, open source package....