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Head to head

Minerva (540B) vs Wu Dao 2.0

Google
Minerva (540B)
June 2022
vs
Beijing Academy of Artificial Intelligence / BAAI
Wu Dao 2.0
May 2021
2.7×10²⁴Training compute (FLOP)1.5×10²⁴
--Training cost$3M

Minerva (540B) (Google) and Wu Dao 2.0 (Beijing Academy of Artificial Intelligence / BAAI) are both frontier AI models. Minerva (540B) was published in June 2022 and Wu Dao 2.0 in May 2021.

Minerva (540B) was trained on 2.7×10²⁴ FLOP, about 1.8x the compute of Wu Dao 2.0 at 1.5×10²⁴ 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
Organization
Beijing Academy of Artificial Intelligence / BAAI
Jun 29, 2022
Published
May 31, 2021
2.7×10²⁴ FLOP
Training compute1.8x
1.5×10²⁴ FLOP
540.4B
Parameters3.2x
1.8T
26B
Dataset size188x
4.9T
Google TPU v4
Training hardware
--
1,024
Chips used
--
696 h
Training time
--
--
Training cost (2023 USD)
$3M
698.4 kW
Training power draw
--
Unreleased
Accessibility
API access
No
Open weights
No
United States
Country
China
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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.