AI models
Viking
Training compute
2.6×10²³ FLOP
Parameters
33B
Published
Apr 4, 2024
Viking is an AI model developed by Silo AI and University of Turku (Finland), first published in April 2024. It works in the language domain, on tasks such as language modeling/generation, language generation and translation.
Training it took an estimated 2.6×10²³ FLOP of compute (estimation method: operation counting). The model has 33,000,000,000 parameters. It was trained on roughly 2T datapoints. Training ran on 1,024 AMD Radeon Instinct MI250X.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Silo AI, University of Turku
- Country of organization
- Finland
- Domain
- Language
- Task
- Language modeling/generation, Language generation, Translation
- Training compute
- 2.6×10²³ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 33,000,000,000
- Dataset size
- 2T
- Training hardware
- AMD Radeon Instinct MI250X
- Chips used
- 1,024
- Training power draw
- 1.0 MW
- 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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