Head to head
Amazon Titan vs PaLM (540B)
4.8×10²⁴Training compute (FLOP)2.5×10²⁴
$8MTraining cost$3M
Amazon Titan (Amazon) and PaLM (540B) (Google Research) are both frontier AI models. Amazon Titan was published in September 2023 and PaLM (540B) in April 2022.
Amazon Titan was trained on 4.8×10²⁴ FLOP, about 1.9x the compute of PaLM (540B) at 2.5×10²⁴ 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
Amazon
Organization
Google Research
Sep 28, 2023
Published
Apr 4, 2022
4.8×10²⁴ FLOP
Training compute1.9x
2.5×10²⁴ FLOP
200B
Parameters2.7x
540.4B
4T
Dataset size5.1x
780B
NVIDIA A100
Training hardware
Google TPU v4
13,760
Chips used2.2x
6,144
1,152 h
Training time
1,536 h
$8M
Training cost (2023 USD)2.6x
$3M
10.9 MW
Training power draw
4.2 MW
API access
Accessibility
Unreleased
No
Open weights
No
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.