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numbat

burner22

~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.

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