Stable Diffusion XL Environmental Impact
Open-source image model — higher energy per image
- Architecture
- Latent Diffusion Model (U-Net based)
- Parameters
- 6.6B
- Provider
- Stability AI
Energy per query
2.9 Wh
10x more than a Google search (0.3 Wh)
CO2 per query
1.2 g
Global Average grid (475 gCO₂/kWh)
Water per query
5 mL
~185 queries to fill 1 litre
Processing location
Self-hosted (varies)
Provider
Stability AI
Category
Image Generation
Grid carbon intensity
475 g CO2/kWh (27% renewable)
How does Stable Diffusion XL compare?
Detailed Breakdown
Energy Consumption
Stable Diffusion XL consumes approximately 2.9 Wh per image at standard settings (30 steps, 1024x1024) based on the Luccioni et al. benchmark on A100 hardware. High-quality configurations (50+ steps, upscaling) can reach 11+ Wh. Being open-source, it's often run on consumer GPUs which may be less power-efficient than data center hardware.
Power Source & Carbon
As an open-source model, Stable Diffusion XL is deployed across diverse infrastructure — personal PCs, cloud providers (RunPod, Replicate, AWS, etc.), and on-premises servers. The carbon impact varies enormously. A user running it on a home PC in Sweden (30 g CO2/kWh) produces roughly 25x less carbon than someone running it on a cloud server in India (700 g CO2/kWh). Stability AI's own hosted service has faced financial difficulties and defaulted on payments to AWS and Google Cloud.
Water Usage
Water consumption is approximately 5.4 mL per image when run in a data center. When run locally on a personal computer, water consumption for cooling is effectively zero since PCs use air cooling. This is one of the key environmental advantages of self-hosted open-source models.
About Stable Diffusion XL
Stable Diffusion XL is an open-source image generation model from Stability AI, released in July 26, 2023, that runs below the category average for energy consumption at 2.9 Wh per query. Because its weights are publicly available, it can be self-hosted on any infrastructure — meaning its carbon footprint depends entirely on where and how you choose to run it. At 6.6B parameters, it open-source image model — higher energy per image.
Stable Diffusion XL in Context
Your yearly Stable Diffusion XL footprint
At 25 queries per day, your annual Stable Diffusion XL usage consumes 26.5 kWh — roughly what a fridge uses in a month. That produces 10.9 kg of CO₂.
Image vs text: the energy gap
Generating one image with Stable Diffusion XL uses 10x more energy than a text conversation with ChatGPT. The diffusion process that creates images requires many iterative passes through the model, each refining the image from noise — far more compute per output than generating text one token at a time.
Key Insights
Stability AI Stable Family
How energy efficiency has evolved across versions.
What does your Stable Diffusion XL usage cost the planet?
Use our calculator to estimate your personal environmental footprint based on how often you use Stable Diffusion XL.
Calculate My ComputeFrequently Asked Questions
How much energy does Stable Diffusion XL use per query?
Each Stable Diffusion XL query consumes approximately 2.9 Wh of energy. This is 10x more than a traditional Google search (~0.3 Wh).
What is Stable Diffusion XL's carbon footprint?
Based on the carbon intensity of Self-hosted (varies), each query produces approximately 1.2 g of CO2. The grid in this region has a carbon intensity of 475 g CO2/kWh with 27% renewable energy.
How much water does Stable Diffusion XL use?
Each query consumes approximately 5 mL of water, primarily used for cooling the data centers that process the request.
How does Stable Diffusion XL compare to a Google search?
A Stable Diffusion XL query uses 10x more than a Google search in terms of energy. A Google search uses approximately 0.3 Wh, while Stable Diffusion XL uses 2.9 Wh.
Technical Details
Architecture
Latent Diffusion Model (U-Net based)
Parameters
6.6B
Release date
2023-07-26
Open source
Yes