In diretta
Head to head

Flan-PaLM 540B vs Wu Dao 2.0

Google
Flan-PaLM 540B
October 2022
vs
Beijing Academy of Artificial Intelligence / BAAI
Wu Dao 2.0
May 2021
2.5×10²⁴Training compute (FLOP)1.5×10²⁴
--Training cost$3M

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

Flan-PaLM 540B was trained on 2.5×10²⁴ FLOP, about 1.6x 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
Oct 20, 2022
Published
May 31, 2021
2.5×10²⁴ FLOP
Training compute1.6x
1.5×10²⁴ FLOP
540B
Parameters3.2x
1.8T
1.4B
Dataset size3500x
4.9T
Google TPU v4
Training hardware
--
512
Chips used
--
37 h
Training time
--
--
Training cost (2023 USD)
$3M
348.3 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.