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Head to head

Gemini 1.0 Ultra vs Nemotron-4 340B

Google DeepMind
Gemini 1.0 Ultra
December 2023
vs
NVIDIA
Nemotron-4 340B
June 2024
5×10²⁵Training compute (FLOP)1.8×10²⁵
$31MTraining cost$21M

Gemini 1.0 Ultra (Google DeepMind) and Nemotron-4 340B (NVIDIA) are both frontier AI models. Gemini 1.0 Ultra was published in December 2023 and Nemotron-4 340B in June 2024.

Gemini 1.0 Ultra was trained on 5×10²⁵ FLOP, about 2.8x 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
Google DeepMind
Organization
NVIDIA
Dec 6, 2023
Published
Jun 14, 2024
5×10²⁵ FLOP
Training compute2.8x
1.8×10²⁵ FLOP
--
Parameters
340B
--
Dataset size
9T
Google TPU v4
Training hardware
NVIDIA H100 SXM5 80GB
57,000
Chips used9.3x
6,144
2,400 h
Training time
2,200 h
$31M
Training cost (2023 USD)1.4x
$21M
38.4 MW
Training power draw
8.5 MW
API access
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.