---
license: other
tags:
  - cosmos
  - world-model
  - gr1
  - robotics
  - diffusion-forcing
---

# Cosmos3-Nano GR-1 — Diffusion-Forcing + StateFix checkpoints

PyTorch **Distributed Checkpoint (DCP)** checkpoints from joint WM + Action SFT of
NVIDIA `Cosmos3-Nano` (Omni-MoT World Foundation Model) on GR-1, using a causal
**diffusion-forcing** schedule with a fixed proprio-state prefix ("statefix").

Each variant is provided at **iteration 20,000** (the latest checkpoint):

| Subfolder | Horizon | chunk_length | latent_t | Training |
|-----------|---------|--------------|----------|----------|
| `h65/`    | 65-frame | 64  | 17 | 8×B200, FSDP, 45,056-token packing |
| `h129/`   | 129-frame | 128 | 33 | 8×B200, FSDP, 45,056-token packing |
| `h65_joint_1000/` | 65-frame | 64 | 17 | 4×B200, FSDP, 45,056-token packing, **joint** diffusion-forcing (WM + action jointly supervised) |

## Layout

Each subfolder mirrors the framework's checkpoint layout (full DCP — model + optimizer +
scheduler + trainer state), so it can be resumed or evaluated directly:

```
<variant>/
  config.yaml, config.pkl, job_env.yaml, launch_info.yaml
  checkpoints/
    latest_checkpoint.txt
    iter_000020000/
      model/      # FSDP-sharded DCP (.distcp shards + .metadata)
      optim/      # optimizer state (enables training resume)
      scheduler/
      trainer/
```

> **Note:** these are *sharded* DCP checkpoints (`.distcp` + `.metadata`), not
> consolidated `safetensors`. Load them with `torch.distributed.checkpoint` via the
> Cosmos3 framework, or consolidate to HF format with
> `cosmos_framework.scripts.export_model`.