## Line Chart: Score vs. Inference-Time Compute
### Overview
The image is a line chart comparing the performance (Score in %) of "Gemini Deep Think (advanced version, Jan 2026)" against "Inference-Time Compute (Log Scale)". A single data point for "Aletheia" is also shown.
### Components/Axes
* **Title:** Implicit, but the chart compares Score vs. Inference-Time Compute.
* **X-axis:** "Inference-Time Compute (Log Scale)". The axis is marked with powers of 2, from 2<sup>0</sup> to 2<sup>11</sup>.
* **Y-axis:** "Score (%)". The axis ranges from 0% to 40% in increments of 10%.
* **Legend:** Located in the bottom-center of the chart.
* Blue line with circle markers: "Gemini Deep Think (advanced version, Jan 2026)"
* Red star marker: "Aletheia"
### Detailed Analysis
* **Gemini Deep Think (advanced version, Jan 2026):** The blue line shows the performance of Gemini Deep Think at different inference-time compute levels.
* At 2<sup>0</sup>, the score is approximately 0%.
* At 2<sup>3</sup>, the score is approximately 19%.
* At 2<sup>4</sup>, the score is approximately 30%.
* At 2<sup>5</sup>, the score is approximately 19%.
* At 2<sup>6</sup>, the score is approximately 21%.
* At 2<sup>7</sup>, the score is approximately 18%.
* At 2<sup>8</sup>, the score is approximately 21%.
* At 2<sup>9</sup>, the score is approximately 22%.
* At 2<sup>10</sup>, the score is approximately 35%.
* At 2<sup>11</sup>, the score is approximately 38%.
The trend is generally increasing, with a dip between 2<sup>4</sup> and 2<sup>7</sup>.
* **Aletheia:** Represented by a red star. The star is located above the 40% mark, near the 2<sup>9</sup> mark on the x-axis. The score is approximately 47%.
### Key Observations
* Gemini Deep Think's performance generally increases with higher inference-time compute, but there's a period of stagnation or decline in the middle range.
* Aletheia's performance is significantly higher than Gemini Deep Think's at the 2<sup>9</sup> compute level.
### Interpretation
The chart suggests that increasing the inference-time compute for Gemini Deep Think generally improves its score, but there are diminishing returns or even temporary setbacks in certain compute ranges. Aletheia, represented by a single data point, outperforms Gemini Deep Think at a similar compute level, indicating it may be a more efficient or advanced model. The single data point for Aletheia makes it difficult to assess its performance across different compute levels. The data suggests that while increasing compute power can improve AI performance, the specific algorithm or model architecture (as represented by Aletheia) can have a significant impact on overall results.
