# Alpamayo 2 Super ![Organization](https://img.shields.io/badge/Org-NVIDIA-76b900) ![License](https://img.shields.io/badge/License-OpenMDW--1.1-2da44e) ![Modality](https://img.shields.io/badge/Modality-Vision%20%2B%20Language%20%2B%20Action-8957e5) > **Quick answer:** Alpamayo 2 Super is NVIDIA's 34B-parameter foundation model for autonomous vehicle development, combining a 32B vision-language backbone (built on Cosmos 3 Super Reasoner) with a 2.3B diffusion action expert. It ranks first on LingoQA among nearly 40 evaluated models (79.2 Lingo-Judge score) and is openly licensed under OpenMDW-1.1 for commercial robotaxi and AV fleet deployment. ## At a Glance **Where Alpamayo 2 Super leads** - #1 on LingoQA among ~40 models evaluated — 79.2 Lingo-Judge score, ahead of Qwen2.5-VL 72B (+17.0 pts), Gemini 2.5 Pro (+15.1 pts), and GPT-4o (+23.2 pts) - Outperforms Qwen3-VL-32B-Instruct across all six NVIDIA multi-task AV metrics: Meta-Action IoU (Longitudinal/Lateral/Lane), Auto-Labeling Accuracy, 2D Visual Grounding, and OOD Reasoning Score - Openly licensed under OpenMDW-1.1 — permits fine-tuning, derivative models, and commercial redistribution - Produces five coupled outputs per driving scenario: trajectory, chain-of-causation reasoning trace, meta-action, auto-label annotations, and grounded VQA answers **Where it lags** - 3x the parameter count (34B) of the smaller Alpamayo 1.5/1 models, requiring significantly more inference compute (measured peak ~72GB device memory on a single H100) - Only validated on NVIDIA H100 80GB HBM3; other GPU architectures not yet tested - Open-Loop minADE_6 at 6.4s of 0.911m indicates trajectory prediction still has meaningful error at longer horizons ## Model Specifications | Field | Value | |---|---| | Organization | NVIDIA | | Parameters | 34B total (32B VLM backbone + 2.3B diffusion action expert) | | Architecture | Vision-Language-Action (VLA); built on Cosmos 3 Super Reasoner | | Modality | Image/video, text, egomotion history → text + trajectory | | License | OpenMDW-1.1 (weights); Apache 2.0 (source code) | | Release date | August 4, 2026 | | Hugging Face | [nvidia/Alpamayo2-Super](https://huggingface.co/nvidia/Alpamayo2-Super) | ## Benchmark Performance Alpamayo 2 Super's own reported evaluations, per the [NVIDIA model card](https://huggingface.co/nvidia/Alpamayo2-Super): | Benchmark | Score | Notes | |---|---|---| | [LingoQA](/benchmarks/lingoqa) | 79.2 (Lingo-Judge) | #1 of ~40 models evaluated | | AlpaSim (closed-loop, 910 scenarios) | 1.50 ± 0.13 | NVIDIA PhysicalAI-AV-NuRec dataset | | Open-loop minADE₆ @ 6.4s | 0.911m | 937 challenging samples, PhysicalAI-AV dataset | | Meta-Action IoU (Longitudinal) | 61.9% | vs. 35.8% for Qwen3-VL-32B-Instruct | | Meta-Action IoU (Lateral) | 74.6% | vs. 47.5% for Qwen3-VL-32B-Instruct | | Meta-Action IoU (Lane) | 73.5% | vs. 68.8% for Qwen3-VL-32B-Instruct | | Auto-Labeling Accuracy | 65.2% | vs. 45.0% for Qwen3-VL-32B-Instruct | | 2D Visual Grounding (IoU) | 71.0% | vs. 17.0% for Qwen3-VL-32B-Instruct | | OOD Reasoning Score | 43.3 | vs. 39.6 for Qwen3-VL-32B-Instruct | *Scores sourced from [NVIDIA's Alpamayo 2 Super model card](https://huggingface.co/nvidia/Alpamayo2-Super) and [NVIDIA blog announcement](https://blogs.nvidia.com/blog/alpamayo-2-super-open-model-now-available/), August 4, 2026.* ## Frequently Asked Questions

What is Alpamayo 2 Super?

Alpamayo 2 Super is NVIDIA's 34B-parameter open foundation model for autonomous vehicle and robotaxi development, combining a vision-language backbone with a diffusion-based action expert to produce trajectories, reasoning traces, meta-actions, auto-labels, and grounded visual answers.

What benchmark does Alpamayo 2 Super lead on?

Alpamayo 2 Super ranks first on LingoQA, an autonomous driving reasoning benchmark, scoring 79.2 on the Lingo-Judge metric among nearly 40 models evaluated — outperforming Qwen2.5-VL 72B, Gemini 2.5 Pro, and GPT-4o.

Is Alpamayo 2 Super free to use commercially?

Yes. Alpamayo 2 Super is released under the OpenMDW-1.1 license, the Linux Foundation's permissive license for open AI model distribution, which permits fine-tuning, derivative models, and commercial redistribution.

Alpamayo 2 Super — Training jobs

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