Amazon Titan (Amazon) and EXAONE 1.0 (LG) are both frontier AI models. Amazon Titan was published in September 2023 and EXAONE 1.0 in December 2021.
Amazon Titan was trained on 4.8 x 10^24 FLOP, about 2.8x 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 | Amazon Titan | EXAONE 1.0 |
|---|---|---|
| Organization | Amazon | LG |
| Published | Sep 28, 2023 | Dec 14, 2021 |
| Training compute | 4.8 x 10^24 FLOP | 1.7 x 10^24 FLOP |
| Parameters | 200B | 300B |
| Dataset size | 4T | — |
| Training hardware | NVIDIA A100 | — |
| Chips used | 13,760 | — |
| Training time | 1.2K h | — |
| Training cost (2023 USD) | $8M | $3M |
| Training power draw | 10.9 MW | — |
| Accessibility | API access | Unreleased |
| Open weights | No | No |
| Country | United States | South Korea |
