Installation¶
Requirements¶
- Python ≥ 3.10
- NVIDIA GPU (24 GB+ for 2B model, 32 GB+ for 8B model)
- CUDA 12.x
Install¶
zsh users
If you see zsh: no matches found, quote the package name: pip install "strands-cosmos"
Platform Compatibility¶
| Platform | GPU | Status |
|---|---|---|
| Desktop Linux x86_64 | A100 / H100 / RTX 4090 | ✅ |
| Jetson AGX Thor | Thor 132 GB | ✅ (with CUBLAS fix) |
| Jetson Orin | Orin 32/64 GB | ✅ (may need CUBLAS fix) |
| macOS (Apple Silicon) | ❌ | No CUDA — use strands-mlx |
Jetson Setup¶
On NVIDIA Jetson devices, PyTorch's pip-bundled CUBLAS may not support the GPU architecture. Run the included fix after install:
# Fix CUBLAS (auto-detects if needed, safe on any platform)
strands-cosmos-fix-cublas
# Or check without fixing:
strands-cosmos-fix-cublas --check
# Revert if needed:
strands-cosmos-fix-cublas --revert
→ See Jetson Deployment Guide for details.
Verify¶
from strands_cosmos import CosmosVisionModel
model = CosmosVisionModel(model_id="nvidia/Cosmos-Reason2-2B")
print("✅ Model loaded successfully")
First run
The first run downloads the model from HuggingFace (~5 GB for 2B). Subsequent runs load from cache.
What Gets Installed¶
graph LR
COSMOS["strands-cosmos"] --> SA["strands-agents<br/><i>Agent framework</i>"]
COSMOS --> HF["transformers<br/><i>Model loading</i>"]
COSMOS --> TORCH["torch<br/><i>GPU inference</i>"]
COSMOS --> TV["torchvision<br/><i>Video decoding</i>"]
style COSMOS fill:#76b900,color:#fff
style SA fill:#264653,color:#fff
What's Next¶
- Quickstart — Your first Cosmos agent in 5 lines
- Video Understanding — Process dashcam, robot, and scene videos
- Jetson Deployment — Run on edge hardware