Amazon Titan (Amazon) and Gemini 1.0 Ultra (Google DeepMind) are both frontier AI models. Amazon Titan was published in September 2023 and Gemini 1.0 Ultra in December 2023.
Gemini 1.0 Ultra was trained on 5 x 10^25 FLOP, about 10.4x the compute of Amazon Titan at 4.8 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 | Gemini 1.0 Ultra |
|---|---|---|
| Organization | Amazon | Google DeepMind |
| Published | Sep 28, 2023 | Dec 6, 2023 |
| Training compute | 4.8 x 10^24 FLOP | 5 x 10^25 FLOP |
| Parameters | 200B | — |
| Dataset size | 4T | — |
| Training hardware | NVIDIA A100 | Google TPU v4 |
| Chips used | 13,760 | 57,000 |
| Training time | 1.2K h | 2.4K h |
| Training cost (2023 USD) | $8M | $31M |
| Training power draw | 10.9 MW | 38.4 MW |
| Accessibility | API access | API access |
| Open weights | No | No |
| Country | United States | United States |
