~14T param, 114 layers, hybrid GDN/MLA, MoE (1,224 experts, top-48 + 1 shared), NVFP4. Internal codename numbat, Anthropic's next Mythos-class training run. numbat is the codename referenced in the Claude Code source leak (Mar 2026). This is a checkpoint from that training run, pulled mid-pretraining.
The 772 shards total ~7.72 TB of tensor data. Each shard is safetensors format, under 10.6 GB per file.
configuration_numbat.py and modeling_numbat.py are included: a complete reference implementation of the checkpoint. Its module tree has an exact slot for every tensor in every shard, so the full checkpoint loads with load_state_dict(strict=True) (and, since the classes derive from PreTrainedModel, also via AutoModelForCausalLM.from_pretrained(..., trust_remote_code=True)). NumbatForCausalLM.forward runs the trunk and NumbatForCausalLM.draft runs the MTP layer.
