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Flan-PaLM 540B vs Nemotron-4 340B

Google
Flan-PaLM 540B
October 2022
vs
NVIDIA
Nemotron-4 340B
June 2024
2.5×10²⁴Training compute (FLOP)1.8×10²⁵
--Training cost$21M

Flan-PaLM 540B (Google) and Nemotron-4 340B (NVIDIA) are both frontier AI models. Flan-PaLM 540B was published in October 2022 and Nemotron-4 340B in June 2024.

Nemotron-4 340B was trained on 1.8×10²⁵ FLOP, about 7.1x the compute of Flan-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
NVIDIA
Oct 20, 2022
Published
Jun 14, 2024
2.5×10²⁴ FLOP
Training compute7.1x
1.8×10²⁵ FLOP
540B
Parameters1.6x
340B
1.4B
Dataset size6429x
9T
Google TPU v4
Training hardware
NVIDIA H100 SXM5 80GB
512
Chips used12x
6,144
37 h
Training time
2,200 h
--
Training cost (2023 USD)
$21M
348.3 kW
Training power draw
8.5 MW
Unreleased
Accessibility
Open weights (unrestricted)
No
Open weights
Yes
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.