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Head to head

Flan-PaLM 540B vs Llama 3.1-405B

Google
Flan-PaLM 540B
October 2022
vs
Meta AI
Llama 3.1-405B
July 2024
2.5×10²⁴Training compute (FLOP)3.8×10²⁵
--Training cost$53M

Flan-PaLM 540B (Google) and Llama 3.1-405B (Meta AI) are both frontier AI models. Flan-PaLM 540B was published in October 2022 and Llama 3.1-405B in July 2024.

Llama 3.1-405B was trained on 3.8×10²⁵ FLOP, about 15.0x 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
Meta AI
Oct 20, 2022
Published
Jul 23, 2024
2.5×10²⁴ FLOP
Training compute15x
3.8×10²⁵ FLOP
540B
Parameters1.3x
405B
1.4B
Dataset size11143x
15.6T
Google TPU v4
Training hardware
NVIDIA H100 SXM5 80GB
512
Chips used32x
16,384
37 h
Training time
2,142 h
--
Training cost (2023 USD)
$53M
348.3 kW
Training power draw
22.6 MW
Unreleased
Accessibility
Open weights (restricted use)
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.