In diretta
Head to head

Flan-PaLM 540B vs GPT-3.5 (davinci-002)

Google
Flan-PaLM 540B
October 2022
vs
OpenAI
GPT-3.5 (davinci-002)
March 2022
2.5×10²⁴Training compute (FLOP)2.6×10²⁴
--Training cost$5M

Flan-PaLM 540B (Google) and GPT-3.5 (davinci-002) (OpenAI) are both frontier AI models. Flan-PaLM 540B was published in October 2022 and GPT-3.5 (davinci-002) in March 2022.

GPT-3.5 (davinci-002) was trained on 2.6×10²⁴ FLOP, essentially the same compute as Flan-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
Google
Organization
OpenAI
Oct 20, 2022
Published
Mar 15, 2022
2.5×10²⁴ FLOP
Training compute
2.6×10²⁴ FLOP
540B
Parameters
--
1.4B
Dataset size
--
Google TPU v4
Training hardware
NVIDIA A100 SXM4 40 GB
512
Chips used
--
37 h
Training time
--
--
Training cost (2023 USD)
$5M
348.3 kW
Training power draw
--
Unreleased
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.