---
license: apache-2.0
language:
- en
base_model:
- nvidia/Cosmos-Reason2-8B
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- text-generation-inference
- llama.cpp
---

# **Cosmos-Reason2-8B-GGUF**

> NVIDIA Cosmos-Reason2-8B is an 8.767B-parameter open vision-language model post-trained from Qwen3-VL-8B-Instruct under the permissive NVIDIA Open Model License (commercially usable with derivative rights), designed for physical AI, robotics, and embodied reasoning with enhanced spatio-temporal understanding, physics-based common sense, object detection (2D/3D localization, bounding boxes), and 256K token long-context support for video/image inputs at FPS=4. It excels in use cases like video analytics agents (root-cause analysis via NVIDIA VSS Blueprint), data curation/annotation (Cosmos Curator for sensor data), and robot planning (Isaac GR00T-Dreams for synthetic trajectories), generating chain-of-thought responses in <think>/<answer> format for deliberate decision-making in unfamiliar environments across datasets like EgoExo4D, PerceptionTest, IntPhys, and CLEVRER. Optimized for NVIDIA Blackwell/Hopper GPUs (32GB+ VRAM, BF16 on Linux/H100/A100) with Transformers inference (max_tokens=4096), it handles mp4 videos/jpg images for text outputs in robotics, AVs, and industrial ops while noting limitations in complex dynamics like fast motion or occlusions.

## Cosmos-Reason2-8B [GGUF]

| File Name | Quant Type | File Size | File Link |
| - | - | - | - |
| Cosmos-Reason2-8B.BF16.gguf | BF16 | 16.4 GB | [Download](https://huggingface.co/prithivMLmods/Cosmos-Reason2-8B-GGUF/blob/main/Cosmos-Reason2-8B.BF16.gguf) |
| Cosmos-Reason2-8B.F16.gguf | F16 | 16.4 GB | [Download](https://huggingface.co/prithivMLmods/Cosmos-Reason2-8B-GGUF/blob/main/Cosmos-Reason2-8B.F16.gguf) |
| Cosmos-Reason2-8B.Q8_0.gguf | Q8_0 | 8.71 GB | [Download](https://huggingface.co/prithivMLmods/Cosmos-Reason2-8B-GGUF/blob/main/Cosmos-Reason2-8B.Q8_0.gguf) |
| Cosmos-Reason2-8B.mmproj-bf16.gguf | mmproj-bf16 | 1.16 GB | [Download](https://huggingface.co/prithivMLmods/Cosmos-Reason2-8B-GGUF/blob/main/Cosmos-Reason2-8B.mmproj-bf16.gguf) |
| Cosmos-Reason2-8B.mmproj-f16.gguf | mmproj-f16 | 1.16 GB | [Download](https://huggingface.co/prithivMLmods/Cosmos-Reason2-8B-GGUF/blob/main/Cosmos-Reason2-8B.mmproj-f16.gguf) |
| Cosmos-Reason2-8B.mmproj-q8_0.gguf | mmproj-q8_0 | 752 MB | [Download](https://huggingface.co/prithivMLmods/Cosmos-Reason2-8B-GGUF/blob/main/Cosmos-Reason2-8B.mmproj-q8_0.gguf) |

## Quants Usage 

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)