实时
Head to head

Gemini 1.0 Ultra vs PaLM 2

Google DeepMind
Gemini 1.0 Ultra
December 2023
vs
Google
PaLM 2
May 2023
5×10²⁵Training compute (FLOP)7.3×10²⁴
$31MTraining cost$5M

Gemini 1.0 Ultra (Google DeepMind) and PaLM 2 (Google) are both frontier AI models. Gemini 1.0 Ultra was published in December 2023 and PaLM 2 in May 2023.

Gemini 1.0 Ultra was trained on 5×10²⁵ FLOP, about 6.8x the compute of PaLM 2 at 7.3×10²⁴ 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 DeepMind
Organization
Google
Dec 6, 2023
Published
May 10, 2023
5×10²⁵ FLOP
Training compute6.8x
7.3×10²⁴ FLOP
--
Parameters
340B
--
Dataset size
3.6T
Google TPU v4
Training hardware
Google TPU v4
57,000
Chips used
--
2,400 h
Training time
--
$31M
Training cost (2023 USD)6.1x
$5M
38.4 MW
Training power draw
--
API access
Accessibility
API access
No
Open weights
No
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.