NVlabs/alpamayo
NVIDIA Alpamayo 1 Nano is an open 10B reasoning VLA model for autonomous vehicles that pairs driving trajectories with Chain-of-Causation reasoning.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 11 contributors on GitHub.
Use Cases & Benefits
- Implements a 10B parameter vision-language-action model for autonomous vehicle trajectory prediction with integrated Chain-of-Causation reasoning.
- Combines driving trajectory forecasting with explicit causal reasoning to improve generalization and interpretability in autonomous driving scenarios.
- Use for research and experimentation in developing reasoning-enhanced end-to-end autonomous driving models using multi-camera video inputs.
- Use for generating reasoning traces alongside predicted vehicle trajectories to support explainability and debugging in autonomous vehicle systems.
- Use for building auto-labeling tools that leverage hybrid human-in-the-loop Chain-of-Causation reasoning for autonomous vehicle datasets.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
Watch-outs
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
Note: Following the release of NVIDIA Alpamayo at CES 2026, Alpamayo-R1 has been renamed to Alpamayo 1.
📖 Please read the HuggingFace Model Card first! The model card contains comprehensive details on model architecture, inputs/outputs, licensing, and tested hardware configurations. This GitHub README focuses on setup, usage, and frequently asked questions.
⚠️ Note: GPUs with less than 24 GB VRAM will likely encounter CUDA out-of-memory errors.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
350+20
Open issues
60-11
Compared with peers in Backend
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| microsoft/VibeVoice | 56.0K | +1.1K | 29 | — |
| NVlabs/alpamayo | 2.1K | — | 17 | — |
| Category median | 56.0K | +2.3K | 29 | — |
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