Model reference · open weights
Cosmos-Reason2 is an open-weight language model from NVIDIA. Cosmos-Reason2-8B (BF16) weighs 17.5 GB; the smallest configuration that runs it is RTX 4090 24 GB.
Summary of the nvidia/Cosmos-Reason2-2B model card, 2026-10-01. The estimate below is for another build of the family.
What it is
| Released by | NVIDIA |
|---|---|
| Released | 2025-12-12 |
| Parameters | 2.4B |
| VRAM | 17.5 GB for the weights |
What it runs on
How much memory each request adds isn't estimated yet for this architecture. The weights need at least the cards below, plus room for the context.
| Card | Weights alone |
|---|---|
| RTX 3060 12 GB … RTX 4060 Ti 16 GB 2 smaller cards | does not fit |
| RTX 3090 24 GB | fits |
| RTX 4090 24 GB | fits |
| RTX 5090 32 GB | fits |
| L40S 48 GB | fits |
| A100 80 GB | fits |
| H100 80 GB | fits |
| RTX PRO 6000 Blackwell 96 GB | fits |
| DGX Spark (GB10) 128 GB unified | fits |
| H200 141 GB | fits |
| B200 180 GB | fits |
Builds
| Build | Params | Precision | Weights | Smallest setup |
|---|---|---|---|---|
| Cosmos-Reason2-2B ↗ | 2.4B | BF16 | 4.9 GB | RTX 3060 12 GB |
| Cosmos-Reason2-8B (above) ↗ | 8.8B | BF16 | 17.5 GB | RTX 4090 24 GB |
| Cosmos-Reason2-32B ↗ | 33.4B | BF16 | 66.7 GB | H100 80 GB |
From the model card
NVIDIA Cosmos Reason 2 is an open, customizable, 32B-parameter reasoning vision language model (VLM) for physical AI and robotics that enables robots and vision AI agents to reason like humans, using prior knowledge, physics understanding and common sense to understand and act in the real world. This model understands space, time, and fundamental physics, and can serve as a planning model to reason what steps an embodied agent might take next.
New features with Cosmos Reason 2:
Use cases:
Explore the Cosmos Cookbook, a technical guide that delivers end-to-end workflows, implementation recipes, and detailed examples for building, fine-tuning, and deploying Cosmos Reason in production-ready environments.
The model is ready for commercial use.
Model Developer: NVIDIA
The Cosmos-Reason2 includes the following model:
[04/28/2026] For comparative evaluation, we present benchmark scores using the Physical AI Bench Leaderboard.
We also evaluated Cosmos-Reason2 against Qwen3-VL across the following domains and categories: General, Robotics, Self-Driving, and Smart Spaces.
| Category | Benchmark | Cosmos-Reason2-32B | Qwen3-VL-32B-Instruct | Cosmos-Reason2-8B | Qwen3-VL-8B-Instruct | Cosmos-Reason2-2B | Qwen3-VL-2B-Instruct |
|---|---|---|---|---|---|---|---|
| General | Overall | 75.85 | 73.07 | 73.73 | 71.98 | 62.21 | 59.60 |
| BlinkDepth | 84.68 | 82.26 | 87.90 | 87.10 | 82.26 | 74.19 | |
| BlinkSpatial | 86.71 | 86.71 | 84.62 | 87.41 | 75.52 | 77.62 | |
| CVBench | 88.01 | 86.74 | 85.60 | 85.17 | 78.74 | 78.67 | |
| VideoPhy2 | 43.98 | 36.57 | 36.80 | 28.24 | 12.33 | 7.92 | |
| Robotics | Overall | 60.60 | 55.06 | 56.90 | 53.08 | 45.52 | 42.07 |
| ERQA | 45.25 | 46.50 | 44.00 | 44.00 | 37.75 | 37.75 | |
| CR Common | 65.89 | 63.41 | 64.24 | 58.44 | 54.30 | 49.67 | |
| CR Embodied | 75.25 | 59.34 | 69.34 | 56.89 | 58.03 | 48.85 | |
| Where2Place | 56.00 | 51.00 | 50.00 | 53.00 | 32.00 | 32.00 | |
| Self-Driving | Overall | 70.15 | 48.08 | 67.85 | 46.38 | 57.37 | 42.73 |
| AV Collision | 72.06 | 37.67 | 74.00 | 34.00 | 74.33 | 36.33 | |
| AV Stop | 69.39 | 38.78 | 57.14 | 36.73 | 38.78 | 32.65 | |
| LingoQA | 69.00 | 67.80 | 72.40 | 68.40 | 59.00 | 59.20 | |
| Smart Spaces | Overall | 77.79 | 47.55 | 69.96 | 42.66 | 64.14 | 36.63 |
| Warehouse AI | *77.79 |
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
How it works