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Gemini 1.0 Ultra vs Minerva (540B)

Google DeepMind
Gemini 1.0 Ultra
December 2023
vs
Google
Minerva (540B)
June 2022
5×10²⁵Training compute (FLOP)2.7×10²⁴
$31MTraining cost--

Gemini 1.0 Ultra (Google DeepMind) and Minerva (540B) (Google) are both frontier AI models. Gemini 1.0 Ultra was published in December 2023 and Minerva (540B) in June 2022.

Gemini 1.0 Ultra was trained on 5×10²⁵ FLOP, about 18.2x the compute of Minerva (540B) at 2.7×10²⁴ FLOP. Training compute is the closest available proxy for how much was invested in a model, though it says nothing on its own about how well that compute was spent.

These two models share no benchmark on which both have been scored, so no direct performance comparison is possible here. The specification table below is a comparison of inputs, not of results.

Specifications
Google DeepMind
Organization
Google
Dec 6, 2023
Published
Jun 29, 2022
5×10²⁵ FLOP
Training compute18x
2.7×10²⁴ FLOP
--
Parameters
540.4B
--
Dataset size
26B
Google TPU v4
Training hardware
Google TPU v4
57,000
Chips used56x
1,024
2,400 h
Training time
696 h
$31M
Training cost (2023 USD)
--
38.4 MW
Training power draw
698.4 kW
API access
Accessibility
Unreleased
No
Open weights
No
United States
Country
United States
Related comparisons
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.