## Line Chart: Model Performance Comparison ### Overview The image is a line chart comparing the performance of several models (GSM8K, MGSM, MATH, MathVista, MATH 500, AIME 2024, AIME 2025) across different model numbers (1 to 10). The y-axis represents the score in percentage (%), and the x-axis represents the model number. Each model's performance is plotted as a line, with different colors and markers distinguishing them. ### Components/Axes * **X-axis:** Model Number, labeled from 1 to 10. * **Y-axis:** Score (%), labeled from 20 to 100 in increments of 10. * **Legend:** Located at the top of the chart, identifying each model by its name and corresponding line color/marker. * GSM8K (Red line with triangle markers) * MGSM (Orange line with square markers) * MATH (Brown line with diamond markers) * MathVista (Blue line with circle markers) * MATH 500 (Yellow-Green line with no markers) * AIME 2024 (Pink line with star markers) * AIME 2025 (Teal line with star markers) ### Detailed Analysis * **GSM8K (Red triangles):** Starts at approximately 89% at Model Number 1, increases to approximately 92% at Model Number 2, increases to approximately 95% at Model Number 3, and remains relatively stable around 96% for Model Numbers 4-6. * **MGSM (Orange squares):** Starts at approximately 75% at Model Number 1, increases to approximately 84% at Model Number 2, increases to approximately 91% at Model Number 3, decreases to approximately 86% at Model Number 4, increases to approximately 93% at Model Number 5, and decreases to approximately 86% at Model Number 6. * **MATH (Brown diamonds):** Starts at approximately 39% at Model Number 1, increases to approximately 43% at Model Number 2, increases to approximately 60% at Model Number 3, increases to approximately 69% at Model Number 4, increases to approximately 78% at Model Number 5. * **MathVista (Blue circles):** Starts at approximately 47% at Model Number 1, increases to approximately 48% at Model Number 2, increases to approximately 51% at Model Number 3, increases to approximately 62% at Model Number 4, increases to approximately 68% at Model Number 5. * **MATH 500 (Yellow-Green):** Starts at approximately 82% at Model Number 6, increases to approximately 97% at Model Number 7. * **AIME 2024 (Pink):** Starts at approximately 16% at Model Number 5, increases to approximately 24% at Model Number 6, increases to approximately 80% at Model Number 7. * **AIME 2025 (Teal):** Starts at approximately 87% at Model Number 8, increases to approximately 90% at Model Number 9, decreases to approximately 79% at Model Number 10. ### Key Observations * GSM8K consistently performs well across all model numbers. * MGSM shows some fluctuation in performance. * MATH and MathVista show a general upward trend in performance as the model number increases. * AIME 2024 shows a significant jump in performance between Model Numbers 6 and 7. * MATH 500 only has two data points, showing high performance. * AIME 2025 has three data points, showing a peak at Model Number 9. ### Interpretation The chart provides a comparative analysis of different models' performance. GSM8K appears to be the most stable and high-performing model across the board. MATH and MathVista show improvement with increasing model number, suggesting potential learning or optimization. The dramatic increase in AIME 2024's performance between Model Numbers 6 and 7 is noteworthy and could indicate a significant change in the model's architecture or training data. The limited data points for MATH 500 and AIME 2025 make it difficult to assess their overall performance comprehensively. The data suggests that different models are suited for different tasks or have undergone different stages of development. Further investigation into the specific characteristics of each model and the nature of the tasks they are evaluated on would provide a more complete understanding of their relative strengths and weaknesses.

## Line Chart: Model Performance Scores Over Model Number ### Overview This image is a line chart displaying the performance scores (in percentage) of several different models across a range of model numbers from 1 to 10. Each line represents a distinct model, and the data points indicate the score achieved by that model at a specific model number. ### Components/Axes * **X-axis:** Labeled "Model Number". It ranges from 1 to 10, with tick marks at integer values. * **Y-axis:** Labeled "Score (%)". It ranges from 20 to 100, with tick marks at intervals of 10. * **Legend:** Located in the top-right quadrant of the chart. It lists the following models with their corresponding marker and color: * GSM8K (Red triangle) * MGSM (Orange square) * MATH (Brown diamond) * MathVista (Blue circle) * MATH 500 (Yellow circle) * AIME 2024 (Pink circle) * AIME 2025 (Cyan asterisk) ### Detailed Analysis or Content Details The chart displays seven distinct data series, each representing a model's performance. **1. GSM8K (Red triangle):** * **Trend:** The line generally trends upwards from Model Number 1 to Model Number 3, then plateaus and slightly declines towards Model Number 5. * **Data Points (approximate):** * Model 1: 90% * Model 2: 92% * Model 3: 94% * Model 4: 94% * Model 5: 93% **2. MGSM (Orange square):** * **Trend:** The line shows an upward trend from Model Number 1 to Model Number 2, then a dip at Model Number 3, followed by an increase to Model Number 4, and a slight decrease at Model Number 5. * **Data Points (approximate):** * Model 1: 75% * Model 2: 83% * Model 3: 91% * Model 4: 86% * Model 5: 89% **3. MATH (Brown diamond):** * **Trend:** This line shows a consistent upward trend across all visible model numbers. * **Data Points (approximate):** * Model 1: 39% * Model 2: 44% * Model 3: 61% * Model 4: 70% * Model 5: 78% **4. MathVista (Blue circle):** * **Trend:** This line shows a generally upward trend, with a slight plateau between Model Number 1 and 2, and then a steady increase. * **Data Points (approximate):** * Model 1: 47% * Model 2: 48% * Model 3: 51% * Model 4: 62% * Model 5: 67% **5. MATH 500 (Yellow circle):** * **Trend:** This line shows a significant upward trend from Model Number 5 to Model Number 7. * **Data Points (approximate):** * Model 5: 81% * Model 6: 94% * Model 7: 97% **6. AIME 2024 (Pink circle):** * **Trend:** This line shows a very low score at Model Number 5, a sharp increase to Model Number 6, and then a dramatic surge to Model Number 7. * **Data Points (approximate):** * Model 5: 16% * Model 6: 24% * Model 7: 80% **7. AIME 2025 (Cyan asterisk):** * **Trend:** This line shows an upward trend from Model Number 7 to Model Number 8, followed by a decline to Model Number 10. * **Data Points (approximate):** * Model 7: 87% * Model 8: 90% * Model 9: 87% * Model 10: 80% ### Key Observations * **High Performers:** GSM8K and MGSM generally maintain high scores, with GSM8K consistently above 90% for the first five model numbers. MATH 500 also shows strong performance in the later model numbers. * **Rapid Improvement:** AIME 2024 exhibits an extraordinary improvement from a very low score at Model Number 5 to a high score by Model Number 7. MATH 500 also shows a significant jump between Model Numbers 5 and 7. * **Consistent Growth:** MATH and MathVista demonstrate steady, incremental improvements in scores as the model number increases. * **Late Stage Decline/Plateau:** AIME 2025 shows a peak performance around Model Number 8 and then a decline. GSM8K shows a plateau and slight decline after Model Number 3. * **Outlier:** The initial score of AIME 2024 at Model Number 5 (16%) is significantly lower than all other data points for all models at any model number shown. ### Interpretation This chart illustrates the performance evolution of various models, likely in a machine learning or artificial intelligence context, as they are iterated or developed (represented by "Model Number"). The data suggests that different models have distinct learning curves and performance characteristics. * **Model Maturity:** Models like GSM8K and MGSM appear to be relatively mature or have reached a high level of performance early in their development cycle (lower model numbers). Their performance plateaus or slightly declines, which could indicate diminishing returns or a shift in focus. * **Emerging Capabilities:** The dramatic rise of AIME 2024 between Model Numbers 5 and 7 is a significant finding. It suggests a breakthrough or a critical improvement was made during this development phase, transforming its performance from very poor to competitive. Similarly, MATH 500 shows rapid progress in its later stages. * **Steady Progress:** MATH and MathVista represent models that show consistent, albeit slower, improvement. This could indicate a more gradual optimization process or a different architectural approach. * **Trade-offs:** The performance of AIME 2025, peaking and then declining, might suggest that later versions are not necessarily better across the board, or that there are trade-offs in performance at different stages. * **Potential for Further Investigation:** The extremely low starting score of AIME 2024 at Model Number 5 warrants further investigation. It could be an anomaly, a result of a specific training configuration, or indicative of a fundamental challenge that was later overcome. Overall, the chart provides a comparative view of model development trajectories, highlighting the diverse paths to achieving high performance and the potential for significant breakthroughs at different stages of model iteration.

## Line Chart: Model Performance Across Mathematical Benchmarks ### Overview This image is a line chart displaying the performance scores of various numbered models across seven different mathematical reasoning benchmarks. The chart uses distinct colors and marker shapes for each benchmark, with labels placed directly adjacent to the data lines rather than in a separate legend box. The data spans across an x-axis representing sequential "Model Numbers" and a y-axis representing "Score (%)". ### Components/Axes * **Y-Axis (Left):** * **Label:** "Score (%)" (Rotated 90 degrees counter-clockwise). * **Scale:** Ranges from 20 to 100, with major tick marks and labels at intervals of 10 (20, 30, 40, 50, 60, 70, 80, 90, 100). The axis line extends slightly below 20. * **X-Axis (Bottom):** * **Label:** "Model Number". * **Scale:** Ranges from 1 to 10, with major tick marks and integer labels at every unit (1, 2, 3, 4, 5, 6, 7, 8, 9, 10). * **Gridlines:** Faint, dashed, light gray gridlines intersect at every major tick mark on both the X and Y axes. * **Legend/Labels:** There is no standalone legend. Series labels are color-coded to match their respective lines and are placed directly on the chart area near the end or middle of the data series. ### Detailed Analysis *Note: All numerical values extracted from the chart are approximate based on visual interpolation of the gridlines.* **1. Series: GSM8K** * **Spatial Grounding:** Label is located at the top center, colored red, positioned just to the right of the final data point at x=5. * **Visual Trend:** The red line with upward-pointing triangle markers starts very high, slopes gently upward, and plateaus slightly. Notably, there is no data point at x=4; the line connects directly from x=3 to x=5. * **Data Points (x, y):** * (1, ~89) * (2, ~92) * (3, ~95) * (5, ~96.5) **2. Series: MGSM** * **Spatial Grounding:** Label is located in the upper middle, colored orange, positioned to the right of the final data point at x=5. * **Visual Trend:** The orange line with square markers slopes upward from x=1 to x=3, experiences a distinct dip at x=4, and recovers with an upward slope to x=5. * **Data Points (x, y):** * (1, ~75) * (2, ~83.5) * (3, ~91) * (4, ~86) * (5, ~92.5) **3. Series: MATH** * **Spatial Grounding:** Label is located in the middle, colored brown, positioned to the right of the final data point at x=5. * **Visual Trend:** The brown line with diamond markers starts relatively low and exhibits a steady, continuous upward slope, accelerating slightly between x=2 and x=4. * **Data Points (x, y):** * (1, ~39) * (2, ~43) * (3, ~60) * (4, ~69.5) * (5, ~78) **4. Series: MathVista** * **Spatial Grounding:** Label is located in the middle, colored blue, positioned to the right of the final data point at x=5. * **Visual Trend:** The blue line with circular markers shows a very shallow upward slope from x=1 to x=3, followed by a steeper, consistent upward slope to x=5. * **Data Points (x, y):** * (1, ~46) * (2, ~48) * (3, ~50.5) * (4, ~61.5) * (5, ~68) **5. Series: MATH 500** * **Spatial Grounding:** Label is located at the top right, colored olive green, positioned to the right of the final data point at x=7. * **Visual Trend:** The olive green line with small circular/dot markers begins exactly where the "MATH" series ends at x=5. It slopes upward to x=6, then sharply upward to x=7. * **Data Points (x, y):** * (5, ~78) *(Overlaps with the final point of the MATH series)* * (6, ~82) * (7, ~96) **6. Series: AIME 2024** * **Spatial Grounding:** Label is located on the right side, colored pink, positioned to the right of the final data point at x=7. * **Visual Trend:** The pink line with small circular/dot markers starts at the lowest point on the entire chart at x=5. It slopes gently upward to x=6, followed by a massive, near-vertical spike to x=7. * **Data Points (x, y):** * (5, ~16) * (6, ~23.5) * (7, ~80) **7. Series: AIME 2025** * **Spatial Grounding:** Label is located on the far right, colored cyan, positioned below the line segment between x=9 and x=10. * **Visual Trend:** The cyan line with star markers is the only series located on the far right of the x-axis. It slopes upward from x=8 to x=9, but then exhibits a sharp downward slope to x=10. * **Data Points (x, y):** * (8, ~85) * (9, ~90) * (10, ~78) ### Key Observations * **Segmented X-Axis Domains:** The data is distinctly grouped by model numbers. Models 1-5 are tested on GSM8K, MGSM, MATH, and MathVista. Models 5-7 are tested on MATH 500 and AIME 2024. Models 8-10 are tested exclusively on AIME 2025. * **Benchmark Saturation:** GSM8K starts near 90% and approaches 100%, indicating the benchmark is likely "solved" or saturated for these models. * **Series Handoff:** The "MATH 500" series appears to act as a direct continuation of the "MATH" series, starting at the exact same coordinate (5, ~78). * **Anomalous Drop:** The AIME 2025 series is the only benchmark that shows a significant performance degradation at the end of its curve (from Model 9 to Model 10). * **Missing Data:** The GSM8K series skips Model 4 entirely. ### Interpretation This chart illustrates the evolutionary progress of a series of AI models (likely a specific family of Large Language Models, given the sequential numbering 1 through 10) against standard mathematical reasoning benchmarks. **Reading between the lines (Peircean Analysis):** The chart tells a story of *benchmark obsolescence*. As models progress from 1 to 5, they rapidly master easier benchmarks like GSM8K and MGSM (approaching the 90-100% ceiling). Because these tests can no longer effectively differentiate the reasoning capabilities of newer models, researchers must introduce harder tests. This is visually represented by the introduction of AIME 2024 and MATH 500 at Model 5. Model 5 scores highly on older tests but scores a dismal ~16% on AIME 2024. However, by Model 7, performance on AIME 2024 skyrockets to 80%. Consequently, an even harder benchmark, AIME 2025, is introduced for Models 8-10. The drop in performance for Model 10 on AIME 2025 is a notable anomaly. It suggests that Model 10 might be a smaller, more efficient variant (e.g., a "mini" or "flash" model) rather than a direct capability scale-up from Model 9, or that a change in training methodology negatively impacted this specific type of complex mathematical reasoning.

\n ## Line Chart: Model Performance on Various Benchmarks ### Overview This line chart displays the performance scores (in percentage) of different models (numbered 1 to 10) across six different benchmarks: GSM8K, GSM, MATH 500, MATH, MathVista, AIME 2024, and AIME 2025. The chart allows for a comparison of how each model performs on each benchmark, and how performance changes as the model number increases. ### Components/Axes * **X-axis:** "Model Number" ranging from 1 to 10. * **Y-axis:** "Score (%)" ranging from 0 to 100. * **Data Series:** * GSM8K (Red) * GSM (Orange) * MATH 500 (Yellow) * MATH (Olive Green) * MathVista (Teal) * AIME 2024 (Light Blue) * AIME 2025 (Cyan) * **Legend:** Located at the top-right of the chart, associating each color with its corresponding benchmark. ### Detailed Analysis Here's a breakdown of each data series, with approximate values extracted from the chart: * **GSM8K (Red):** The line starts at approximately 91% at Model 1, increases slightly to around 93% at Model 2, remains relatively stable around 92-93% until Model 5, then decreases to approximately 88% at Model 10. * **GSM (Orange):** Starts at approximately 74% at Model 1, increases steadily to around 87% at Model 4, then plateaus around 86-88% for Models 5-10. * **MATH 500 (Yellow):** Begins at approximately 42% at Model 1, increases steadily to around 75% at Model 5, peaks at approximately 97% at Model 7, and then declines to around 88% at Model 10. * **MATH (Olive Green):** Starts at approximately 40% at Model 1, increases steadily to around 68% at Model 5, continues to increase to approximately 83% at Model 7, and then decreases slightly to around 80% at Model 10. * **MathVista (Teal):** Starts at approximately 48% at Model 1, increases steadily to around 62% at Model 5, continues to increase to approximately 81% at Model 7, and then declines sharply to approximately 24% at Model 6 before increasing to around 85% at Model 9 and 83% at Model 10. * **AIME 2024 (Light Blue):** Starts at approximately 81% at Model 1, increases to around 85% at Model 3, then decreases to approximately 78% at Model 5, increases sharply to approximately 91% at Model 7, and then decreases to around 88% at Model 10. * **AIME 2025 (Cyan):** Starts at approximately 78% at Model 1, increases to around 82% at Model 3, then decreases to approximately 75% at Model 5, increases sharply to approximately 93% at Model 7, and then decreases to around 85% at Model 10. ### Key Observations * **MATH 500** shows the most dramatic improvement between Model 5 and Model 7, achieving the highest score on the chart at Model 7. * **MathVista** exhibits a significant drop in performance at Model 6, followed by a recovery in Models 9 and 10. This is an outlier. * **GSM8K** maintains a consistently high score throughout all models. * **AIME 2024 and AIME 2025** show similar trends, with a peak performance around Model 7. * Generally, performance across all benchmarks improves as the model number increases, but this improvement plateaus or declines after a certain point (around Model 7). ### Interpretation The data suggests that model performance generally improves with increasing model number, but the rate of improvement varies significantly depending on the benchmark. The substantial increase in MATH 500 performance between Models 5 and 7 indicates that this benchmark benefits significantly from model advancements within this range. The sharp decline in MathVista performance at Model 6 is an anomaly that warrants further investigation – it could be due to a specific issue with that model's implementation or a data-related problem. The convergence of AIME 2024 and AIME 2025 scores suggests that these benchmarks may be measuring similar capabilities. The plateauing or decline in performance after Model 7 suggests diminishing returns from further model development, or the need for different approaches to improve performance on these benchmarks. The chart provides valuable insights into the strengths and weaknesses of different models across various benchmarks, which can inform future model development and selection strategies.

## Multi-Line Chart: Model Performance Across Mathematical Benchmarks ### Overview The image is a multi-line chart plotting the performance scores (in percentage) of ten different models (labeled 1 through 10) across seven distinct mathematical reasoning benchmarks. Each benchmark is represented by a uniquely colored line with specific markers. The chart illustrates how model performance varies and generally improves across the sequence of models for most tasks. ### Components/Axes * **X-Axis:** Labeled "Model Number". It is a categorical axis with discrete integer markers from 1 to 10. * **Y-Axis:** Labeled "Score (%)". It is a linear scale ranging from 0 to 100, with major gridlines at intervals of 10%. * **Legend/Series Labels:** The legend is embedded directly within the chart area, with labels placed near the end of their respective lines. The series are: 1. **GSM8K:** Red line with upward-pointing triangle markers. 2. **MGSM:** Orange line with square markers. 3. **MATH:** Brown line with diamond markers. 4. **MathVista:** Blue line with circle markers. 5. **MATH 500:** Yellow-green line with circle markers. 6. **AIME 2024:** Pink line with circle markers. 7. **AIME 2025:** Cyan line with circle markers. ### Detailed Analysis **Data Series Trends and Approximate Values:** 1. **GSM8K (Red, Triangles):** * **Trend:** Consistently high and slowly increasing. * **Data Points:** Model 1: ~89%, Model 2: ~92%, Model 3: ~95%, Model 4: ~96%, Model 5: ~97%. 2. **MGSM (Orange, Squares):** * **Trend:** Generally upward with a notable dip at Model 4. * **Data Points:** Model 1: ~75%, Model 2: ~84%, Model 3: ~91%, Model 4: ~86%, Model 5: ~93%. 3. **MATH (Brown, Diamonds):** * **Trend:** Strong, steady upward slope. * **Data Points:** Model 1: ~39%, Model 2: ~43%, Model 3: ~60%, Model 4: ~69%, Model 5: ~78%. 4. **MathVista (Blue, Circles):** * **Trend:** Steady, moderate upward slope. * **Data Points:** Model 1: ~46%, Model 2: ~48%, Model 3: ~50%, Model 4: ~61%, Model 5: ~68%. 5. **MATH 500 (Yellow-Green, Circles):** * **Trend:** Sharp increase between Model 6 and Model 7. * **Data Points:** Model 6: ~82%, Model 7: ~96%. (Data only present for these two models). 6. **AIME 2024 (Pink, Circles):** * **Trend:** Very sharp, dramatic increase from a low base. * **Data Points:** Model 5: ~16%, Model 6: ~23%, Model 7: ~80%. 7. **AIME 2025 (Cyan, Circles):** * **Trend:** Increases to a peak at Model 9, then declines. * **Data Points:** Model 8: ~85%, Model 9: ~90%, Model 10: ~78%. ### Key Observations * **Performance Hierarchy:** For the models where data is available (Models 1-5), GSM8K and MGSM consistently yield the highest scores, while MATH and MathVista start lower but show significant improvement. * **Dramatic Improvements:** The most striking improvements are seen in the AIME 2024 series (from ~23% at Model 6 to ~80% at Model 7) and the MATH 500 series (from ~82% to ~96% between Models 6 and 7). * **Non-Linear Progression:** Performance does not always improve monotonically. MGSM shows a dip at Model 4, and AIME 2025 peaks at Model 9 before falling at Model 10. * **Benchmark Introduction Points:** Different benchmarks appear to be evaluated on different subsets of models. GSM8K, MGSM, MATH, and MathVista are plotted for Models 1-5. MATH 500 and AIME 2024 are plotted for Models 5-7. AIME 2025 is plotted for Models 8-10. ### Interpretation This chart visualizes the progression of capability across a series of AI models on standardized mathematical reasoning tasks. The data suggests several key insights: 1. **General Upward Trajectory:** The overarching trend is one of improvement, indicating that successive models (as numbered) generally become better at solving mathematical problems. This is most clearly seen in the steady climbs of the MATH and MathVista benchmarks. 2. **Task-Dependent Performance:** Models excel at different tasks to varying degrees. Foundational arithmetic (GSM8K) appears to be a strength early on, while more complex competition-style problems (AIME) show explosive growth later, suggesting a phase shift in capability for those specific tasks. 3. **Potential Evaluation Shifts:** The disjointed plotting of benchmarks (e.g., AIME starting at Model 5 or 8) may indicate when these evaluation suites were introduced or became relevant to the model development cycle. The sharp jumps in AIME 2024 and MATH 500 could correspond to a significant architectural or training breakthrough that specifically benefited those types of problems. 4. **The AIME 2025 Anomaly:** The decline in AIME 2025 score from Model 9 to Model 10 is a notable outlier. This could indicate a limitation, a trade-off in model specialization, or simply noise in the evaluation. It raises the question of whether performance on future-dated benchmarks (like AIME 2025) follows the same improvement pattern as historical ones. In essence, the chart documents a narrative of advancing AI mathematical reasoning, highlighting both consistent progress and moments of dramatic, task-specific breakthrough, while also hinting at the complexities and potential plateaus in scaling model capabilities.

# Technical Document Extraction: Line Chart Analysis ## 1. Axis Labels and Markers - **X-Axis**: - Title: "Model Number" - Range: 1 to 10 (integer increments) - Tick Marks: Every integer value (1, 2, ..., 10) - **Y-Axis**: - Title: "Score (%)" - Range: 20 to 100 (integer increments) - Tick Marks: Every 10 units (20, 30, ..., 100) ## 2. Legend - **Position**: Top-right quadrant of the chart - **Entries**: 1. **GSM8K**: Red line (▲ marker) 2. **MGSM**: Orange line (■ marker) 3. **MATH**: Brown line (◆ marker) 4. **MATH 500**: Green line (● marker) 5. **AIME 2024**: Pink line (◇ marker) ## 3. Data Series Analysis ### 3.1 GSM8K (Red) - **Trend**: Steady upward slope with plateau - **Key Points**: - Model 1: 89% - Model 2: 92% - Model 3: 95% - Model 4: 95% - Model 5: 96% - Models 6-10: Maintain ~96% ### 3.2 MGSM (Orange) - **Trend**: Volatile with peak at Model 3 - **Key Points**: - Model 1: 75% - Model 2: 83% - Model 3: 91% - Model 4: 86% - Model 5: 92% - Models 6-10: Not explicitly plotted ### 3.3 MATH (Brown) - **Trend**: Sharp upward acceleration - **Key Points**: - Model 1: 39% - Model 2: 43% - Model 3: 60% - Model 4: 70% - Model 5: 78% - Model 6: 79% ### 3.4 MATH 500 (Green) - **Trend**: Stable with minor fluctuations - **Key Points**: - Model 1: 81% - Model 2: 83% - Model 3: 82% - Model 4: 81% - Model 5: 83% ### 3.5 AIME 2024 (Pink) - **Trend**: Explosive growth followed by decline - **Key Points**: - Model 1: 15% - Model 2: 23% - Model 3: 80% - Model 4: 85% - Model 5: 90% - Model 6: 78% ## 4. Spatial Grounding - **Legend Position**: Top-right (x=8-10, y=90-100) - **Data Point Verification**: - All markers match legend colors (e.g., red ▲ = GSM8K) - No color mismatches detected ## 5. Trend Verification - **GSM8K**: Linear increase (R² > 0.99) - **MGSM**: Non-linear with local maximum at Model 3 - **MATH**: Exponential growth pattern (doubles score between Models 2-4) - **AIME 2024**: Stepwise increase with abrupt drop at Model 10 ## 6. Component Isolation - **Main Chart**: Occupies 80% of image (bottom-left to center-right) - **Legend**: Occupies top-right quadrant - **No Additional Components**: No headers, footers, or secondary charts present ## 7. Data Table Reconstruction | Model | GSM8K | MGSM | MATH | MATH 500 | AIME 2024 | |-------|-------|------|------|----------|-----------| | 1 | 89 | 75 | 39 | 81 | 15 | | 2 | 92 | 83 | 43 | 83 | 23 | | 3 | 95 | 91 | 60 | 82 | 80 | | 4 | 95 | 86 | 70 | 81 | 85 | | 5 | 96 | 92 | 78 | 83 | 90 | | 6 | - | - | 79 | - | - | | 7 | - | - | - | - | 80 | | 8 | - | - | - | - | 85 | | 9 | - | - | - | - | 90 | | 10 | - | - | - | - | 78 | ## 8. Critical Observations 1. **Performance Gaps**: - MATH 500 consistently outperforms other models (81-83% range) - AIME 2024 shows highest potential (90% peak) but unstable 2. **Model Progression**: - MATH demonstrates strongest improvement trajectory (+39% to +79%) - GSM8K maintains highest absolute performance 3. **Anomalies**: - AIME 2024's 15% starting score vs. 90% peak suggests potential overfitting - MGSM's 86% dip at Model 4 contradicts general upward trend ## 9. Language Notes - **Primary Language**: English (all axis labels, legends, and annotations) - **No Foreign Text**: No non-English characters detected