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Gemini 1.0 Ultra vs Llama 3.1-405B

Google DeepMind
Gemini 1.0 Ultra
December 2023
vs
Meta AI
Llama 3.1-405B
July 2024
5×10²⁵Training compute (FLOP)3.8×10²⁵
$31MTraining cost$53M

Gemini 1.0 Ultra (Google DeepMind) and Llama 3.1-405B (Meta AI) are both frontier AI models. Gemini 1.0 Ultra was published in December 2023 and Llama 3.1-405B in July 2024.

Gemini 1.0 Ultra was trained on 5×10²⁵ FLOP, about 1.3x the compute of Llama 3.1-405B at 3.8×10²⁵ 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
Google DeepMind
Organization
Meta AI
Dec 6, 2023
Published
Jul 23, 2024
5×10²⁵ FLOP
Training compute1.3x
3.8×10²⁵ FLOP
--
Parameters
405B
--
Dataset size
15.6T
Google TPU v4
Training hardware
NVIDIA H100 SXM5 80GB
57,000
Chips used3.5x
16,384
2,400 h
Training time
2,142 h
$31M
Training cost (2023 USD)1.7x
$53M
38.4 MW
Training power draw
22.6 MW
API access
Accessibility
Open weights (restricted use)
No
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.