AI models
SILC-S* (86M)
Training compute
10²² FLOP
Parameters
86M
Published
Oct 20, 2023
SILC-S* (86M) is an AI model developed by ETH Zurich, DeepMind, Google and Technical University of Munich (Switzerland, United Kingdom, United States and Germany), first published in October 2023. It works in the vision domain, on tasks such as image classification and image segmentation.
Training it took an estimated 10²² FLOP of compute. The model has 86,000,000 parameters. Training ran on 256 Google TPU v4 for about 120 hours.
Access: Unreleased. Its weights are not openly released. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- ETH Zurich, DeepMind, Google, Technical University of Munich
- Country of organization
- Switzerland, United Kingdom, United States, Germany
- Domain
- Vision
- Task
- Image classification, Image segmentation
- Training compute
- 10²² FLOP
- Parameters
- 86,000,000
- Training hardware
- Google TPU v4
- Chips used
- 256
- Training time
- 120 h
- Training power draw
- 172.8 kW
- Model accessibility
- Unreleased
- Open weights
- No
- Epoch confidence
- Confident
More from ETH Zurich,DeepMind,Google,Technical University of Munich
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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