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FLAN 137B vs GPT-3.5 (davinci-002)

Google Research
FLAN 137B
September 2021
vs
OpenAI
GPT-3.5 (davinci-002)
March 2022
2×10²⁴Training compute (FLOP)2.6×10²⁴
--Training cost$5M

FLAN 137B (Google Research) and GPT-3.5 (davinci-002) (OpenAI) are both frontier AI models. FLAN 137B was published in September 2021 and GPT-3.5 (davinci-002) in March 2022.

GPT-3.5 (davinci-002) was trained on 2.6×10²⁴ FLOP, about 1.3x the compute of FLAN 137B at 2×10²⁴ 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 Research
Organization
OpenAI
Sep 3, 2021
Published
Mar 15, 2022
2×10²⁴ FLOP
Training compute1.3x
2.6×10²⁴ FLOP
137B
Parameters
--
2.5T
Dataset size
--
Google TPU v3
Training hardware
NVIDIA A100 SXM4 40 GB
--
Training cost (2023 USD)
$5M
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.