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Head to head

Llama 3.1-405B vs Nemotron-4 340B

Meta AI
Llama 3.1-405B
July 2024
vs
NVIDIA
Nemotron-4 340B
June 2024
3.8×10²⁵Training compute (FLOP)1.8×10²⁵
$53MTraining cost$21M

Llama 3.1-405B (Meta AI) and Nemotron-4 340B (NVIDIA) are both frontier AI models. Llama 3.1-405B was published in July 2024 and Nemotron-4 340B in June 2024.

Llama 3.1-405B was trained on 3.8×10²⁵ FLOP, about 2.1x the compute of Nemotron-4 340B at 1.8×10²⁵ 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
Meta AI
Organization
NVIDIA
Jul 23, 2024
Published
Jun 14, 2024
3.8×10²⁵ FLOP
Training compute2.1x
1.8×10²⁵ FLOP
405B
Parameters1.2x
340B
15.6T
Dataset size1.7x
9T
NVIDIA H100 SXM5 80GB
Training hardware
NVIDIA H100 SXM5 80GB
16,384
Chips used2.7x
6,144
2,142 h
Training time
2,200 h
$53M
Training cost (2023 USD)2.5x
$21M
22.6 MW
Training power draw
8.5 MW
Open weights (restricted use)
Accessibility
Open weights (unrestricted)
Yes
Open weights
Yes
United States
Country
United States
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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.