GPT-3.5 (davinci-002) (OpenAI) and Minerva (540B) (Google) are both frontier AI models. GPT-3.5 (davinci-002) was published in March 2022 and Minerva (540B) in June 2022.
Minerva (540B) was trained on 2.7 x 10^24 FLOP, essentially the same compute as GPT-3.5 (davinci-002) at 2.6 x 10^24 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.
| Field | GPT-3.5 (davinci-002) | Minerva (540B) |
|---|---|---|
| Organization | OpenAI | |
| Published | Mar 15, 2022 | Jun 29, 2022 |
| Training compute | 2.6 x 10^24 FLOP | 2.7 x 10^24 FLOP |
| Parameters | — | 540.4B |
| Dataset size | — | 26B |
| Training hardware | NVIDIA A100 SXM4 40 GB | Google TPU v4 |
| Chips used | — | 1,024 |
| Training time | — | 696 h |
| Training cost (2023 USD) | $5M | — |
| Training power draw | — | 698.4 kW |
| Accessibility | API access | Unreleased |
| Open weights | No | No |
| Country | United States | United States |
