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Open-source models for autonomous driving

Autonomous driving models perceive the road, plan motion and generate scenes for simulation. This field serves developers of self-driving vehicles, warehouse machinery and research teams. Check compatibility with your sensors, compute requirements and the license terms.

3 open model families in this collection.Updated 22 Sep 2026Open the full catalog with filters
Autonomous driving2020–2026

comma.ai openpilot (supercombo)

comma.ai · USA

An open driver assistance system: a neural network keeps the lane and controls speed from a camera, plus a driver attention monitoring model. The models live right in the repository and are updated constantly.

  • A research testbed for driver assistance systems
  • Studying driver attention monitoring with an in-cabin camera
  • Comparison with your own lane-keeping algorithms
Sizes
compact, designed for an in-vehicle device
Hardware
from: Laptop
Commercial use allowedDetails
Autonomous driving2025–2026

NVIDIA Alpamayo

NVIDIA · USA

Vision-language-action models for self-driving vehicles: they plan a trajectory from camera video and explain the decision in text. Used to develop and test autopilot systems, not as a ready-made autopilot.

  • Auto-labeling camera recordings to train your own driver assistance systems
  • Analyzing complex road scenes with text explanations
  • Testing autopilot systems in simulation on rare scenarios
Sizes
10B – 34B
Hardware
from: 1 GPU
Commercial use with conditionsDetails
Autonomous driving2026

Qwen-Drive

Alibaba (Qwen team) · China

An autonomous driving model based on Qwen3.5-4B: 3D detection of objects around the vehicle, answers to questions about the road scene and trajectory planning in one model.

  • A perception and planning prototype for autonomous vehicles on closed sites
  • Answering questions about camera recordings when reviewing incidents
  • Labeling road scenes to train your own models
Sizes
4B
Hardware
from: 1 GPU
Commercial use allowedDetails

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