Alpamayo-R1-10B

Alpamayo 1 Code** | **Paper** _Note: Following the release of NVIDIA Alpamayo at CES 2026, Alpamayo-R1 has been renamed to Alpamayo 1._ Model Overview Description: Alpamayo 1 integrates Chain-of-Causation reasoning with trajectory planning to enhance decision-making in complex autonomous-driving scenarios. Alpamayo 1 (v1.0) was developed by NVIDIA as a vision-language-action (VLA) model that bridges interpretable reasoning with precise vehicle control for autonomous-driving applications. This model is ready for non-commercial use. Commercial licensing available upon request. License: The model weights are released under a non-commercial license. The inference code is released under the Apache 2.0 license. Deployment Geography: Global Use Case: Researchers and autonomous-driving practitioners who are developing and evaluating VLA models for autonomous-driving scenarios, particularly for handling rare, long-tail events. Release Date: Hugging Face 12/03/2025 via this repository. Inference Code: GitHub: https://github.com/NVlabs/alpamayo Reference: Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail Model Architecture: Architecture Type:** Transformer Network Architecture:** A VLA model based on Cosmos-Reason and featuring a diffusion-based trajectory decoder. This model was developed based on:** Cosmos-Reason (VLM backbone) with a diffusion-based action decoder Number of model parameters:** Backbone: 8.2B parameters Action Expert: 2.3B parameters Input(s): Input Type(s):** Image/Video, Text, Egomotion History Input Format(s):** Image: Red, Green, Blue (RGB) Text: String Egomotion History: Floating-point values `(x, y, z), R_rot` Input Parameters:** Image: Two-dimensional (2D), multi-camera, multi-timestep Text: One-dimensional (1D) Egomotion History: Three-dimensional (3D) translation and nine-dimensional (9D, 3x3) rotation, multi-timestep Other Properties Related to Input:** Multi-camera images (4 cameras: front-