EXAONE 1.0 (LG) and GPT-4 (Mar 2023) (OpenAI) are both frontier AI models. EXAONE 1.0 was published in December 2021 and GPT-4 (Mar 2023) in March 2023.
GPT-4 (Mar 2023) was trained on 2.1 x 10^25 FLOP, about 12.4x the compute of EXAONE 1.0 at 1.7 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 | EXAONE 1.0 | GPT-4 (Mar 2023) |
|---|---|---|
| Organization | LG | OpenAI |
| Published | Dec 14, 2021 | Mar 15, 2023 |
| Training compute | 1.7 x 10^24 FLOP | 2.1 x 10^25 FLOP |
| Parameters | 300B | 1.8T |
| Dataset size | — | 5.4T |
| Training hardware | — | NVIDIA A100 SXM4 40 GB |
| Chips used | — | 25,000 |
| Training time | — | 2.3K h |
| Training cost (2023 USD) | $3M | $37M |
| Training power draw | — | 19.9 MW |
| Accessibility | Unreleased | API access |
| Open weights | No | No |
| Country | South Korea | United States |
