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EXAONE 1.0 vs Gemini 1.0 Ultra

LG
EXAONE 1.0
December 2021
vs
Google DeepMind
Gemini 1.0 Ultra
December 2023
1.7×10²⁴Training compute (FLOP)5×10²⁵
$3MTraining cost$31M

EXAONE 1.0 (LG) and Gemini 1.0 Ultra (Google DeepMind) are both frontier AI models. EXAONE 1.0 was published in December 2021 and Gemini 1.0 Ultra in December 2023.

Gemini 1.0 Ultra was trained on 5×10²⁵ FLOP, about 29.5x the compute of EXAONE 1.0 at 1.7×10²⁴ 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
LG
Organization
Google DeepMind
Dec 14, 2021
Published
Dec 6, 2023
1.7×10²⁴ FLOP
Training compute29x
5×10²⁵ FLOP
300B
Parameters
--
--
Training hardware
Google TPU v4
--
Chips used
57,000
--
Training time
2,400 h
$3M
Training cost (2023 USD)11x
$31M
--
Training power draw
38.4 MW
Unreleased
Accessibility
API access
No
Open weights
No
South Korea
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.