According to NVIDIA's official blog, the company released Alpamayo 2 Super — a model built on NVIDIA Cosmos 3 Super Reasoner — on Hugging Face under the OpenMDW-1.1 license, permitting commercial fine-tuning and redistribution. NVIDIA said the model ranks first on the LingoQA benchmark among nearly 40 models, and the wider Alpamayo family has surpassed 500,000 Hugging Face downloads.
Technical Specifications and Model Iteration
According to NVIDIA's blog post announcing the release, Alpamayo 2 Super is "built on NVIDIA Cosmos 3 Super Reasoner and post-trained with reinforcement learning." NVIDIA said the model "advances the AV ecosystem on two fronts: open commercial licensing and leading multitask capabilities for autonomous driving" — a characterization from the company's own announcement rather than an independent assessment.
On scale, NVIDIA stated that Alpamayo 2 Super "offers 3x the scale of the 10-billion-parameter NVIDIA Alpamayo 1.5 and Alpamayo 1 models," marking it as the largest model in the Alpamayo lineup to date, though NVIDIA did not disclose an absolute parameter count for the new model.
Open Licensing and Commercial Deployment: Hugging Face Release and the OpenMDW License
NVIDIA announced that Alpamayo 2 Super is "available now for commercial use" as part of what the company calls "the most-adopted open reasoning models for autonomous driving on Hugging Face." The model is distributed under OpenMDW-1.1, which NVIDIA describes as "the Linux Foundation's permissive license for open AI model distributions," covering "fine-tuning, derivative models and commercial redistribution."
NVIDIA further stated that this licensing approach now extends beyond the single model: "The OpenMDW license is now being applied across the entire Alpamayo model family so developers can deploy any of the models commercially without requiring additional permissions." This means earlier releases in the family are covered by the same commercial terms as the new Alpamayo 2 Super.
Benchmark Performance: Vision-Language Understanding and Autonomous-Driving Evaluations
NVIDIA reported that Alpamayo 2 Super "ranks first on LingoQA, an autonomous driving reasoning benchmark, among nearly 40 models evaluated." In NVIDIA's own testing using the Lingo-Judge metric, the company said the model outperformed three named competitors by specific margins:
| Comparison Model | Alpamayo 2 Super's Margin (Lingo-Judge, per NVIDIA testing) |
|---|
| Qwen2.5-VL 72B | +17.0 points |
| Gemini 2.5 Pro | +15.1 points |
| GPT-4o | +23.2 points |
NVIDIA said these results demonstrate what it called "state-of-the-art reasoning for driving-centric scenarios." The company also stated that "Alpamayo 2 Super also ranks first across all autonomous driving benchmarks evaluated by NVIDIA," a claim NVIDIA said "underscor[es] its leading performance across a broad range of AV capabilities." All of these benchmark results come from NVIDIA's own testing, as disclosed in its announcement.
Purpose-Built Architecture: Five Coupled Outputs and Automated Training Data
Per NVIDIA's description, Alpamayo 2 Super produces five tightly coupled outputs for each driving situation: a trajectory describing the vehicle's planned path; a chain-of-causation (CoC) trace explaining the reasoning behind a decision; a meta-action (such as yield, lane change, or stop) capturing the model's intent; reasoning auto-labels that generate CoC annotations for training and validation data; and visual question-answering responses with 2D visual grounding linking answers to specific regions in camera images.
NVIDIA said this grounding capability allows the model to function as an automated annotator: "By linking its reasoning to specific regions in camera images, the model can transform raw driving clips into richer training data, compressing annotation cycles from months to days."
Safety Design: ISO/PAS 8800 Alignment and Halos Validation
Building on the chain-of-causation trace described above, NVIDIA stated that these "CoC traces integrate with NVIDIA Halos safety-validation workflows and support AI safety aligned with ISO/PAS 8800 requirements, providing a stronger foundation for AV safety engineering." This connects the model's reasoning-output architecture (the CoC trace) directly to a named industry safety standard and NVIDIA's own Halos validation tooling.
Open Ecosystem, Supporting Tools, and Adoption Metrics
NVIDIA listed three components supporting the Alpamayo open ecosystem: "NVIDIA AlpaSim, which provides closed-loop simulation. NVIDIA AlpaGym, which enables high-throughput reinforcement learning. NVIDIA Physical AI Open Datasets, which supply data for training and testing."
On adoption, NVIDIA reported that "Alpamayo has already surpassed 500,000 downloads on Hugging Face, reinforcing its position as the most-adopted open reasoning model family for autonomous driving on the platform." That download figure applies to the Alpamayo family as a whole, not to Alpamayo 2 Super alone.
What This Means
Taken together, the facts NVIDIA disclosed describe a layered release: a commercially unrestricted license (OpenMDW-1.1) now applied retroactively across the entire Alpamayo family, paired with benchmark claims — first on LingoQA among nearly 40 models, and first across every NVIDIA-evaluated AV benchmark — that come exclusively from NVIDIA's own internal testing rather than a third-party leaderboard. The model's chain-of-causation output is positioned both as a safety-engineering artifact tied to ISO/PAS 8800 and Halos validation, and as a data-generation tool that NVIDIA says shortens annotation cycles from months to days. The 500,000-download figure for the broader Alpamayo family is the only independent-platform signal in NVIDIA's announcement; the performance and safety claims rest on NVIDIA's own reporting.