Cosmos Diffusion 7B
Stableby NVIDIA
7B diffusion model from NVIDIA's Cosmos platform for physical AI and world modeling. Generates physically plausible videos from text descriptions. Part of NVIDIA's Physical AI initiative.
- 7B DiT — NVIDIA Physical AI
- Physically plausible world simulation
- Part of Cosmos platform for robotics and simulation
- Text-to-world generation
Your hardware
Detecting...
Image Quality Benchmarks
Measured quality metrics for Cosmos Diffusion 7B outputs.
How often humans prefer this model's output (0-100%)
Visual quality and composition rating (5-9 scale)
VRAM by Scenario
VRAM estimates at FP16 and FP8 precision. FP8 uses ~40% less memory with minimal quality loss. Grade shows how well each GPU handles the generation workload.
FP16 (full precision)
| Scenario | VRAM | RTX 4090 24GB | RTX 3060 12GB | RTX 4060 8GB | MacBook Pro M4 Pro 24GB |
|---|---|---|---|---|---|
| 512×512 · 25 frames | 25.9 GB | B | F | F | F |
| 768×512 · 25 frames | 26.3 GB | B | F | F | F |
| 768×512 · 100 frames | 27.2 GB | B | F | F | F |
| 1280×720 · 25 frames | 27.5 GB | B | F | F | F |
FP8 (quantized — ~40% less VRAM)
| Scenario | VRAM | RTX 4090 24GB | RTX 3060 12GB | RTX 4060 8GB | MacBook Pro M4 Pro 24GB |
|---|---|---|---|---|---|
| 512×512 · 25 frames | 13.7 GB | S | B | F | S |
| 768×512 · 25 frames | 14.0 GB | S | D | F | A |
| 768×512 · 100 frames | 14.9 GB | S | D | F | A |
| 1280×720 · 25 frames | 15.2 GB | S | D | F | A |
Optimization Tips
Turbo / LCM distillation
Use distilled scheduler at 4-8 steps for faster iteration
Run with Python
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained(
"nvidia/Cosmos-1.0-Diffusion-7B-Text2World",
torch_dtype=torch.float16
)
pipe.to("cuda")
frames = pipe(
prompt="your prompt here",
num_inference_steps=35,
guidance_scale=7.5,
num_frames=57,
).frames[0]
# Save frames or export as videoGet started
Setup instructions for running Cosmos Diffusion 7B locally
1. Download the model
Get the checkpoint from HuggingFace
2. Place in:
ComfyUI/models/checkpoints/3. Launch ComfyUI
python main.pyMemory Breakdown
VRAM allocation for 25 frames at 768×512 on RTX 4090 24GB
Estimated Generation Time
25 frames at 768×512, 30 steps, FP16.
Sample Outputs
Available Formats & Downloads
Download Cosmos Diffusion 7B in different precisions. Lower precision = less VRAM but slight quality loss.
| Formato | Precisão | Tamanho | Provedor | |
|---|---|---|---|---|
| safetensorsRecomendado | BF16 | 14.0 GB | official | Baixar |
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Frequently asked questions
FAQ — Cosmos Diffusion 7B
How much VRAM does Cosmos Diffusion 7B need for video?
Cosmos Diffusion 7B (7B parameters) requires approximately 26.3 GB of VRAM at FP16 precision for generating 25 frames at 768×512. Video generation typically requires more VRAM than image generation due to temporal attention layers.
Can I run Cosmos Diffusion 7B on RTX 4090?
Cosmos Diffusion 7B can run on the RTX 4090 with sequential offloading, though video generation will be significantly slower than native fit.
How long does it take to generate a video with Cosmos Diffusion 7B?
On a reference GPU (RTX 4090 24GB), Cosmos Diffusion 7B generates a 25-frame video at 768×512 in approximately ~4m 38s at FP16 with 30 inference steps. Faster GPUs with higher memory bandwidth will reduce generation time.
What resolution and frame count does Cosmos Diffusion 7B support?
Cosmos Diffusion 7B supports up to 1024×576 resolution and 57 frames per generation at 24 FPS. Higher resolutions and frame counts require proportionally more VRAM.
About Cosmos Diffusion 7B
See also