Moonshot AI released the Kimi K3 weights on Hugging Face last week, and the repo immediately became one of the largest open-weight checkpoints most of us have ever seen. If you're trying to figure out what exactly shipped and how the files fit together, the official repo is the source of truth — but it's also ~1.5 TB and 100+ files, so orienting yourself takes time.
I put together an independent reference called OpenK3 that maps out the current Hugging Face revision, the file layout, and the license summary. This post walks through what I learned while building it.
What actually shipped
The moonshotai/Kimi-K3 repo contains the full weights for a 2.8T-parameter sparse MoE model. At the time of writing, the checkpoint is organized around 96 safetensors shards plus the usual supporting files: config.json, tokenizer files, model index mappings, and evaluation metadata.
Key points if you're planning to download:
