# Technical Data Extraction: Resolved by Turn Histograms This document contains a detailed extraction of data from two side-by-side histograms comparing the performance of two AI models (GPT-4 and Claude 3 Opus) in terms of how many "turns" it takes to resolve a task. ## 1. General Metadata * **Image Type:** Comparative Histograms (Frequency Distributions). * **Primary Language:** English. * **Visual Style:** Blue bars with black outlines on a white background. * **Common Y-Axis Label:** Count (Frequency of occurrences). * **Common X-Axis Label:** Turn (The number of interactions/steps taken). --- ## 2. Component Analysis: Left Chart (GPT-4) ### Header Information * **Title:** Resolved by Turn (GPT 4, Full) ### Axis Scales * **Y-Axis (Count):** Ranges from 0 to 60, with major tick marks every 10 units (0, 10, 20, 30, 40, 50, 60). * **X-Axis (Turn):** Ranges from approximately 4 to 40, with major tick marks every 5 units (5, 10, 15, 20, 25, 30, 35, 40). ### Data Distribution & Trends * **Trend Description:** The distribution is unimodal and right-skewed. There is a significant peak (mode) between turns 8 and 13, followed by a steady decline with a small secondary bump around turn 18-20. The data trails off significantly after turn 35. * **Estimated Data Points (Bin Counts):** * **Turns 4-6:** ~24 * **Turns 6-8:** ~27 * **Turns 8-11 (Peak):** ~59 * **Turns 11-13:** ~55 * **Turns 13-15:** ~23 * **Turns 15-18:** ~20 * **Turns 18-20:** ~26 * **Turns 20-23:** ~8 * **Turns 23-25:** ~3 * **Turns 25-28:** ~9 * **Turns 28-30:** ~7 * **Turns 30-32:** ~5 * **Turns 32-34:** ~13 * **Turns 34-37:** ~3 * **Turns 37-40:** ~4 --- ## 3. Component Analysis: Right Chart (Claude 3 Opus) ### Header Information * **Title:** Resolved by Turn (Claude 3 Opus, Full) ### Axis Scales * **Y-Axis (Count):** Ranges from 0 to 30+, with major tick marks every 5 units (0, 5, 10, 15, 20, 25, 30). Note: The highest bar exceeds the 30 mark. * **X-Axis (Turn):** Ranges from approximately 4 to 26, with major tick marks every 5 units (5, 10, 15, 20, 25). ### Data Distribution & Trends * **Trend Description:** The distribution is multimodal and more compressed than the GPT-4 chart. It shows three distinct peaks: a primary peak around turn 10-11, a secondary peak at turn 14, and a tertiary peak at turn 16-17. The resolution process for this model appears to conclude much earlier (by turn 26) compared to GPT-4 (which goes to turn 40). * **Estimated Data Points (Bin Counts):** * **Turns 4-5:** ~3 * **Turns 6-7:** ~3 * **Turns 7-8:** ~12 * **Turns 8-10:** ~16 * **Turns 10-11 (Highest Peak):** ~32 * **Turns 11-13:** ~8 * **Turns 13-14 (Secondary Peak):** ~29 * **Turns 14-16:** ~9 * **Turns 16-17 (Tertiary Peak):** ~27 * **Turns 17-19:** ~7 * **Turns 19-20:** ~12 * **Turns 20-22:** ~9 * **Turns 22-23:** ~17 * **Turns 23-25:** ~7 * **Turns 25-26:** ~1 --- ## 4. Comparative Summary | Feature | GPT-4 (Full) | Claude 3 Opus (Full) | | :--- | :--- | :--- | | **Max Turn Count** | ~40 Turns | ~26 Turns | | **Highest Frequency** | ~59 (at Turn 10) | ~32 (at Turn 10) | | **Distribution Shape** | Single dominant peak, long tail. | Multiple distinct peaks, shorter range. | | **Efficiency Indicator** | Resolves most tasks by turn 15, but has many outliers. | Resolves tasks in a tighter window, finishing all by turn 26. |

## Bar Charts: Resolved by Turn (GPT 4, Full) and Resolved by Turn (Claude 3 Opus, Full) ### Overview The image contains two side-by-side bar charts comparing the distribution of task resolutions across turns for two AI models: GPT 4 and Claude 3 Opus. Both charts use "Turn" as the x-axis and "Count" as the y-axis, with distinct ranges and distributions for each model. --- ### Components/Axes #### Left Chart (GPT 4, Full) - **Title**: "Resolved by Turn (GPT 4, Full)" - **X-axis (Turn)**: Discrete intervals from 5 to 40 (inclusive), labeled in increments of 5. - **Y-axis (Count)**: Continuous scale from 0 to 60, labeled in increments of 10. - **Bars**: Blue, with heights corresponding to resolution counts per turn. - **Key Data Points**: - Turn 10: ~60 (peak) - Turn 11: ~55 - Turn 15: ~20 - Turn 20: ~25 - Turn 30: ~5 - Turn 35: ~3 - Turn 40: ~2 #### Right Chart (Claude 3 Opus, Full) - **Title**: "Resolved by Turn (Claude 3 Opus, Full)" - **X-axis (Turn)**: Discrete intervals from 5 to 25 (inclusive), labeled in increments of 5. - **Y-axis (Count)**: Continuous scale from 0 to 30, labeled in increments of 5. - **Bars**: Blue, with heights corresponding to resolution counts per turn. - **Key Data Points**: - Turn 10: ~30 (peak) - Turn 14: ~28 - Turn 18: ~25 - Turn 20: ~12 - Turn 22: ~18 - Turn 24: ~15 - Turn 25: ~2 --- ### Detailed Analysis #### Left Chart (GPT 4, Full) - **Trend**: - Sharp peak at Turn 10 (~60 resolutions), followed by a rapid decline. - Secondary peak at Turn 20 (~25 resolutions). - Counts drop below 10 after Turn 25, with minimal activity by Turn 40. - **Distribution**: - High concentration of resolutions in early turns (5–15), with a long tail extending to Turn 40. #### Right Chart (Claude 3 Opus, Full) - **Trend**: - Peak at Turn 10 (~30 resolutions), followed by a secondary peak at Turn 14 (~28 resolutions). - Gradual decline after Turn 18, with a resurgence at Turn 22 (~18 resolutions). - Counts remain above 5 until Turn 25. - **Distribution**: - More evenly distributed across turns compared to GPT 4, with resolutions spread from Turn 5 to 25. --- ### Key Observations 1. **GPT 4 Dominance in Early Turns**: - GPT 4 resolves significantly more tasks by Turn 10 (~60 vs. ~30 for Claude 3 Opus). - Resolutions drop sharply after Turn 11, suggesting rapid initial progress but limited sustained performance. 2. **Claude 3 Opus’ Gradual Resolution**: - Resolutions are more evenly distributed, with no single turn exceeding 30. - Secondary peaks at Turns 14 and 22 indicate prolonged task resolution over time. 3. **X-axis Range Discrepancy**: - GPT 4’s x-axis extends to Turn 40, while Claude 3 Opus stops at Turn 25. This may reflect differences in task complexity or game length. 4. **Y-axis Scaling**: - GPT 4’s y-axis scales to 60, while Claude 3 Opus’ scales to 30, emphasizing GPT 4’s higher resolution capacity. --- ### Interpretation - **Efficiency vs. Consistency**: - GPT 4 demonstrates higher efficiency in resolving tasks early (Turn 10 peak), but its performance declines rapidly. This suggests a "burst" approach, excelling in initial problem-solving but struggling with sustained effort. - Claude 3 Opus shows more consistent resolution across turns, with no single turn dominating. This implies a steadier, more methodical approach to task resolution. - **Turn Range Implications**: - The extended x-axis for GPT 4 (up to Turn 40) may indicate it handles longer or more complex tasks, whereas Claude 3 Opus’ shorter range (up to Turn 25) suggests shorter or simpler scenarios. - **Practical Implications**: - GPT 4 might be better suited for tasks requiring rapid initial solutions (e.g., debugging, quick decision-making). - Claude 3 Opus could be preferable for tasks demanding prolonged engagement and incremental progress (e.g., strategic planning, iterative development). - **Anomalies**: - GPT 4’s sharp decline after Turn 10 contrasts with Claude 3 Opus’ gradual resolution, highlighting divergent problem-solving strategies. - The resurgence in Claude 3 Opus’ resolutions at Turn 22 (~18) suggests a late-stage effort spike, possibly indicating adaptive behavior. --- ### Conclusion The charts reveal distinct performance profiles between GPT 4 and Claude 3 Opus. GPT 4 excels in early-stage task resolution but falters in sustained effort, while Claude 3 Opus maintains steadier performance over time. These differences underscore the importance of model selection based on task requirements: speed vs. consistency.