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Flan-PaLM 540B vs PaLM (540B)

Google
Flan-PaLM 540B
October 2022
vs
Google Research
PaLM (540B)
April 2022
2.5×10²⁴Training compute (FLOP)2.5×10²⁴
--Training cost$3M

Flan-PaLM 540B (Google) and PaLM (540B) (Google Research) are both frontier AI models. Flan-PaLM 540B was published in October 2022 and PaLM (540B) in April 2022.

Flan-PaLM 540B was trained on 2.5×10²⁴ FLOP, essentially the same compute as PaLM (540B) at 2.5×10²⁴ 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
Google Research
Oct 20, 2022
Published
Apr 4, 2022
2.5×10²⁴ FLOP
Training compute
2.5×10²⁴ FLOP
540B
Parameters
540.4B
1.4B
Dataset size557x
780B
Google TPU v4
Training hardware
Google TPU v4
512
Chips used12x
6,144
37 h
Training time
1,536 h
--
Training cost (2023 USD)
$3M
348.3 kW
Training power draw
4.2 MW
Unreleased
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.