AI models
NeuroChess
Training compute
8.6×10¹¹ FLOP
Parameters
72.3K
Published
Dec 2, 1994
NeuroChess is an AI model, first published in December 1994. It works in the games domain, on tasks such as chess. It counts among the frontier models: the systems trained with the most compute of their moment.
Training it took an estimated 8.6×10¹¹ FLOP of compute (estimation method: hardware). The model has 72,251 parameters. It was trained on roughly 9.6M datapoints.
Epoch AI rates the confidence of this record as speculative.
Full record
- Domain
- Games
- Task
- Chess
- Training compute
- 8.6×10¹¹ FLOP
- Compute estimation method
- Hardware
- Parameters
- 72,251
- Dataset size
- 9.6M
- Epoch confidence
- Speculative
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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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