AI models
Wuerstchen
Training compute
8.3×10²¹ FLOP
Parameters
1B
Published
Sep 29, 2023
Wuerstchen is an AI model developed by Technische Hochschule Ingolstadt, University of Montreal / Université de Montréal, Mila - Quebec AI (originally Montreal Institute for Learning Algorithms), Polytechnique Montreal and Wand Technologies (Germany, Canada and United States), first published in September 2023. It works in the image generation domain, on tasks such as text-to-image and image generation.
Training it took an estimated 8.3×10²¹ FLOP of compute (estimation method: hardware). The model has 1,000,000,000 parameters.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Technische Hochschule Ingolstadt, University of Montreal / Université de Montréal, Mila - Quebec AI (originally Montreal Institute for Learning Algorithms), Polytechnique Montreal, Wand Technologies
- Country of organization
- Germany, Canada, United States
- Domain
- Image generation
- Task
- Text-to-image, Image generation
- Training compute
- 8.3×10²¹ FLOP
- Compute estimation method
- Hardware
- Parameters
- 1,000,000,000
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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