{"slug": "nvidia-releases-alpamayo-2-super-a-34b-open-vision-language-action-model-for-and", "title": "NVIDIA Releases Alpamayo 2 Super: A 34B Open Vision-Language-Action Model for Robotaxis and Autonomous Driving Under OpenMDW-1.1", "summary": "NVIDIA released Alpamayo 2 Super, a 34B-parameter vision-language-action model for autonomous driving, under the OpenMDW-1.1 license, enabling commercial use. The model, built on a 32B Cosmos 3 Super Reasoner backbone and a 2.3B diffusion action decoder, achieves a LingoQA Lingo-Judge score of 79.2, ranking first among nearly 40 models, and an AlpaSim score of 1.50 ± 0.13. It outputs trajectories, Chain-of-Causation traces, meta-actions, auto-labels, and grounded visual question answering from full-surround camera video.", "body_md": "NVIDIA has released ** Alpamayo 2 Super**, a\n\n[34B-parameter vision-language-action (VLA) mode](https://blogs.nvidia.com/blog/alpamayo-2-super-open-model-now-available/)l for autonomous driving, under an open commercial license. The stated design target is the long-tail events: rare, multi-agent situations that conventional detection-and-prediction stacks handle poorly. The model pairs a 32B VLM backbone, built on NVIDIA Cosmos 3 Super Reasoner and post-trained with reinforcement learning, with a 2.3B diffusion-based action decoder. From one pass over full-surround camera video it emits a planned trajectory, a causal explanation of that trajectory, and a meta-action.\n\n**Is it deployable**\n\nYes, and for commercial use from day one. The weights are released under OpenMDW-1.1, the Linux Foundation’s permissive license for open model distributions; source code is Apache 2.0. The license covers fine-tuning, derivative models and commercial redistribution. NVIDIA is applying OpenMDW across the entire Alpamayo family, so earlier releases introduced for R&D are now deployable commercially without additional permission.\n\n**Inputs, outputs and training data**\n\nInputs are multi-camera RGB video, text, and egomotion history with timestamps. The validated public notebook profiles use six cameras and four historical frames per camera. Egomotion is 3D translation plus a 3×3 rotation matrix, multi-timestep.\n\nThe trajectory API returns 64 waypoints spanning 0.1 to 6.4 seconds at 0.1-second intervals. Each waypoint carries ego-frame XYZ and a 3×3 rotation matrix.\n\nTraining data is roughly 115,000 hours of multi-camera driving video with egomotion and trajectory annotations. It includes about 3,700,000 Chain-of-Causation (CoC) traces — structured, causally linked explanations of driving decisions. Image training data exceeds one billion images.\n\n**Benchmarks**\n\nOn [LingoQA](https://github.com/wayveai/LingoQA), Alpamayo 2 Super records a Lingo-Judge score of 79.2 and ranks first among nearly 40 models evaluated. In NVIDIA’s testing it beat Qwen2.5-VL 72B by 17.0 points, Gemini 2.5 Pro by 15.1, and GPT-4o by 23.2.\n\nTwo more numbers matter for planning work. Closed-loop evaluation with [AlpaSim](https://github.com/NVlabs/alpasim) on 910 scenarios from the [PhysicalAI-AV-NuRec](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles-NuRec) dataset gives an AlpaSim score of 1.50 ± 0.13. Open-loop evaluation on 937 challenging samples from the [PhysicalAI-AV](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles) dataset gives minADE₆ at 6.4s of 0.911m.\n\n**Five outputs from one model**\n\nFor each driving situation, the model produces a trajectory, a CoC trace explaining the decision, a meta-action such as yield or lane change, reasoning auto-labels, and visual question answering with 2D grounding.\n\nThat combination is what makes the release interesting operationally. Developers can tie what the model observed to the action it chose. CoC traces integrate with [NVIDIA Halos](https://www.nvidia.com/en-us/ai-trust-center/halos/autonomous-vehicles/) safety-validation workflows and support AI safety aligned with ISO/PAS 8800.\n\nUsed as an autolabeler on proprietary fleet data, NVIDIA says the model compresses annotation cycles from months to days.\n\n**Interactive explainer**\n\n**Key Takeaways**\n\n- 34B VLA model — 32B Cosmos 3 Super Reasoner backbone plus a 2.3B diffusion action expert.\n- OpenMDW-1.1 weights and Apache 2.0 code; commercial use and redistribution allowed, no extra permission needed.\n- LingoQA Lingo-Judge 79.2, first among nearly 40 models; AlpaSim 1.50 ± 0.13; minADE₆ 0.911m at 6.4s.\n- One pass yields trajectory, Chain-of-Causation trace, meta-action, auto-labels, and grounded VQA.\n- Cloud-scale model tested on 1× H100 80GB at 72,115 MiB peak; distill it for in-car inference.\n\nCheck out the** **[ NVIDIA blog](https://blogs.nvidia.com/blog/alpamayo-2-super-open-model-now-available/) and\n\n**Hugging Face model card****.** Also, feel free to follow us on\n\n**and don’t forget to join our**[Twitter](https://x.com/intent/follow?screen_name=marktechpost)\n\n**and Subscribe to**\n\n[150k+ML SubReddit](https://www.reddit.com/r/machinelearningnews/)**. 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The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.", "url": "https://wpnews.pro/news/nvidia-releases-alpamayo-2-super-a-34b-open-vision-language-action-model-for-and", "canonical_source": "https://www.marktechpost.com/2026/08/05/nvidia-alpamayo-2-super-open-vla-model-autonomous-driving/", "published_at": "2026-08-05 08:25:11+00:00", "updated_at": "2026-08-05 08:47:46.091712+00:00", "lang": "en", "topics": ["artificial-intelligence", "autonomous-vehicles", "large-language-models", "generative-ai", "ai-products"], "entities": ["NVIDIA", "Alpamayo 2 Super", "Cosmos 3 Super Reasoner", "OpenMDW-1.1", "Linux Foundation", "LingoQA", "AlpaSim", "PhysicalAI-AV-NuRec"], "alternates": {"html": "https://wpnews.pro/news/nvidia-releases-alpamayo-2-super-a-34b-open-vision-language-action-model-for-and", "markdown": "https://wpnews.pro/news/nvidia-releases-alpamayo-2-super-a-34b-open-vision-language-action-model-for-and.md", "text": "https://wpnews.pro/news/nvidia-releases-alpamayo-2-super-a-34b-open-vision-language-action-model-for-and.txt", "jsonld": "https://wpnews.pro/news/nvidia-releases-alpamayo-2-super-a-34b-open-vision-language-action-model-for-and.jsonld"}}