◷ Awaiting GPU grant
🌌 Cosmos3-Super-Text2Image
A text-to-image demo for nvidia/Cosmos3-Super-Text2Image, NVIDIA's 64B omnimodal world model for Physical AI.
Status
The Gradio app is written and pushed — see app.py. It is
waiting on GPU hardware. Once a ZeroGPU grant is attached, the README frontmatter
flips from sdk: static to sdk: gradio and the demo goes live.
Why it needs a large GPU
| Parameters | 64B (Mixture-of-Transformers) |
| BF16 checkpoint | ~131 GB |
| NVIDIA's tested recipe | 4×H200 / 8×H100 |
ZeroGPU xlarge | 96 GB |
| NVFP4 quantized transformer | ~36 GB |
BF16 does not fit on any single ZeroGPU slice and the model has no Inference
Provider, so the demo hosts it directly. NVFP4 weight-only quantization via
torchao brings it within budget. NVIDIA officially tests this
checkpoint only at BF16, so expect some quality drift.