## Bar Chart: Model Accuracy vs. Difficulty Level ### Overview The image presents a series of bar charts comparing the accuracy of different language models (GPT-4o-mini, Gemini 2.0 Flash, Mistral Small 3.2 24B, Gemma 3 27B, and Llama 4 Maverick) across five difficulty levels. Each chart displays the accuracy achieved by four different methods (PoT, CR, MACM, and IIPC) for each difficulty level. ### Components/Axes * **Title:** Each chart has a title indicating the language model being evaluated (e.g., "GPT-4o-mini"). * **X-axis:** "Difficulty Level" with values 1 to 5. * **Y-axis:** "Accuracy" ranging from 0.0 to 1.0. * **Legend:** Located at the bottom of the image, mapping colors to methods: * Blue: PoT * Orange: CR * Green: MACM * Red: IIPC ### Detailed Analysis #### GPT-4o-mini * **Trend:** Accuracy generally decreases as difficulty level increases for all methods. * **PoT (Blue):** Starts at 93.55% at difficulty 1, decreasing to 60.47% at difficulty 5. * **CR (Orange):** Starts at 91.40% at difficulty 1, decreasing to 50.17% at difficulty 5. * **MACM (Green):** Starts at 92.11% at difficulty 1, decreasing to 43.52% at difficulty 5. * **IIPC (Red):** Starts at 94.27% at difficulty 1, decreasing to 58.80% at difficulty 5. #### Gemini 2.0 Flash * **Trend:** Accuracy remains relatively high across all difficulty levels, with a slight decrease at higher levels. * **PoT (Blue):** Starts at 96.06% at difficulty 1, decreasing to 85.05% at difficulty 5. * **CR (Orange):** Starts at 95.70% at difficulty 1, decreasing to 79.73% at difficulty 5. * **MACM (Green):** Starts at 94.98% at difficulty 1, decreasing to 77.41% at difficulty 5. * **IIPC (Red):** Starts at 96.77% at difficulty 1, decreasing to 87.38% at difficulty 5. #### Mistral Small 3.2 24B * **Trend:** Accuracy decreases as difficulty level increases for all methods. * **PoT (Blue):** Starts at 97.13% at difficulty 1, decreasing to 76.08% at difficulty 5. * **CR (Orange):** Starts at 92.11% at difficulty 1, decreasing to 66.45% at difficulty 5. * **MACM (Green):** Starts at 92.47% at difficulty 1, decreasing to 63.79% at difficulty 5. * **IIPC (Red):** Starts at 96.77% at difficulty 1, decreasing to 80.07% at difficulty 5. #### Gemma 3 27B * **Trend:** Accuracy decreases as difficulty level increases for all methods. * **PoT (Blue):** Starts at 97.13% at difficulty 1, decreasing to 75.08% at difficulty 5. * **CR (Orange):** Starts at 95.34% at difficulty 1, decreasing to 70.76% at difficulty 5. * **MACM (Green):** Starts at 95.70% at difficulty 1, decreasing to 71.10% at difficulty 5. * **IIPC (Red):** Starts at 95.34% at difficulty 1, decreasing to 79.40% at difficulty 5. #### Llama 4 Maverick * **Trend:** Accuracy remains relatively high until difficulty level 4, then decreases. * **PoT (Blue):** Starts at 95.34% at difficulty 1, decreasing to 74.09% at difficulty 5. * **CR (Orange):** Starts at 95.70% at difficulty 1, decreasing to 74.42% at difficulty 5. * **MACM (Green):** Starts at 96.06% at difficulty 1, decreasing to 72.43% at difficulty 5. * **IIPC (Red):** Starts at 96.06% at difficulty 1, decreasing to 80.73% at difficulty 5. ### Key Observations * **General Trend:** Most models show a decrease in accuracy as the difficulty level increases. * **Model Performance:** Gemini 2.0 Flash generally maintains higher accuracy across all difficulty levels compared to the other models. GPT-4o-mini shows the most significant drop in accuracy as difficulty increases. * **Method Comparison:** The relative performance of PoT, CR, MACM, and IIPC varies across models and difficulty levels, but there isn't a consistently superior method. ### Interpretation The charts illustrate how the accuracy of different language models is affected by the difficulty of the task. The decreasing accuracy with increasing difficulty suggests that these models struggle with more complex problems. Gemini 2.0 Flash appears to be more robust to increasing difficulty compared to the other models tested. The different methods (PoT, CR, MACM, IIPC) represent different approaches to solving the tasks, and their varying performance highlights the importance of selecting the appropriate method for a given model and task difficulty. The significant drop in accuracy for GPT-4o-mini at higher difficulty levels suggests that this model may be more sensitive to task complexity than the others.

## Bar Charts: Model Accuracy by Difficulty Level ### Overview This image displays a collection of grouped bar charts, each representing the accuracy of a specific language model across five different difficulty levels. The charts are arranged in a grid, with a legend at the bottom indicating the color coding for four different metrics: PoT, CR, MACM, and IIPC. ### Components/Axes **General Chart Elements (consistent across all charts):** * **Y-axis Title:** "Accuracy" * **Y-axis Scale:** Ranges from 0.0 to 1.0, with major tick marks at 0.0, 0.2, 0.4, 0.6, 0.8, and 1.0. * **X-axis Title:** "Difficulty Level" * **X-axis Markers:** Labeled 1, 2, 3, 4, and 5, representing increasing difficulty. * **Legend:** Located at the bottom center of the image. * **PoT:** Blue bars * **CR:** Orange bars * **MACM:** Green bars * **IIPC:** Red bars **Individual Chart Titles:** 1. GPT-4o-mini 2. Gemini 2.0 Flash 3. Mistral Small 3.2 24B 4. Gemma 3 27B 5. Llama 4 Maverick ### Detailed Analysis or Content Details **1. GPT-4o-mini** * **Trend:** Accuracy generally decreases as difficulty level increases for all metrics. * **Difficulty Level 1:** * PoT: 93.55% (±0.5%) * CR: 91.40% (±0.5%) * MACM: 92.11% (±0.5%) * IIPC: 94.27% (±0.5%) * **Difficulty Level 2:** * PoT: 91.69% (±0.5%) * CR: 87.38% (±0.5%) * MACM: 91.03% (±0.5%) * IIPC: 84.05% (±0.5%) * **Difficulty Level 3:** * PoT: 81.73% (±0.5%) * CR: 75.75% (±0.5%) * MACM: 77.08% (±0.5%) * IIPC: 86.05% (±0.5%) * **Difficulty Level 4:** * PoT: 73.09% (±0.5%) * CR: 66.00% (±0.5%) * MACM: 75.75% (±0.5%) * IIPC: 60.47% (±0.5%) * **Difficulty Level 5:** * PoT: 50.17% (±0.5%) * CR: 43.52% (±0.5%) * MACM: 58.80% (±0.5%) * IIPC: 53.57% (±0.5%) **2. Gemini 2.0 Flash** * **Trend:** Accuracy remains very high and relatively stable across difficulty levels 1-4, with a noticeable drop at difficulty level 5. * **Difficulty Level 1:** * PoT: 96.06% (±0.5%) * CR: 95.70% (±0.5%) * MACM: 94.98% (±0.5%) * IIPC: 96.77% (±0.5%) * **Difficulty Level 2:** * PoT: 98.01% (±0.5%) * CR: 95.35% (±0.5%) * MACM: 96.01% (±0.5%) * IIPC: 97.01% (±0.5%) * **Difficulty Level 3:** * PoT: 93.36% (±0.5%) * CR: 92.67% (±0.5%) * MACM: 91.03% (±0.5%) * IIPC: 96.01% (±0.5%) * **Difficulty Level 4:** * PoT: 90.70% (±0.5%) * CR: 89.04% (±0.5%) * MACM: 90.03% (±0.5%) * IIPC: 93.69% (±0.5%) * **Difficulty Level 5:** * PoT: 85.05% (±0.5%) * CR: 79.73% (±0.5%) * MACM: 77.41% (±0.5%) * IIPC: 87.38% (±0.5%) **3. Mistral Small 3.2 24B** * **Trend:** Accuracy generally decreases as difficulty level increases, with a more pronounced drop from level 4 to 5. * **Difficulty Level 1:** * PoT: 97.13% (±0.5%) * CR: 92.11% (±0.5%) * MACM: 92.47% (±0.5%) * IIPC: 96.77% (±0.5%) * **Difficulty Level 2:** * PoT: 94.02% (±0.5%) * CR: 91.36% (±0.5%) * MACM: 90.70% (±0.5%) * IIPC: 96.01% (±0.5%) * **Difficulty Level 3:** * PoT: 94.02% (±0.5%) * CR: 88.37% (±0.5%) * MACM: 83.72% (±0.5%) * IIPC: 93.02% (±0.5%) * **Difficulty Level 4:** * PoT: 87.38% (±0.5%) * CR: 80.40% (±0.5%) * MACM: 80.73% (±0.5%) * IIPC: 88.70% (±0.5%) * **Difficulty Level 5:** * PoT: 76.08% (±0.5%) * CR: 66.45% (±0.5%) * MACM: 63.79% (±0.5%) * IIPC: 80.07% (±0.5%) **4. Gemma 3 27B** * **Trend:** Accuracy is high and relatively stable for difficulty levels 1-3, followed by a significant drop at levels 4 and 5. * **Difficulty Level 1:** * PoT: 97.13% (±0.5%) * CR: 95.34% (±0.5%) * MACM: 95.70% (±0.5%) * IIPC: 95.34% (±0.5%) * **Difficulty Level 2:** * PoT: 96.35% (±0.5%) * CR: 95.02% (±0.5%) * MACM: 94.35% (±0.5%) * IIPC: 96.68% (±0.5%) * **Difficulty Level 3:** * PoT: 93.69% (±0.5%) * CR: 91.69% (±0.5%) * MACM: 90.70% (±0.5%) * IIPC: 95.02% (±0.5%) * **Difficulty Level 4:** * PoT: 83.39% (±0.5%) * CR: 83.06% (±0.5%) * MACM: 82.39% (±0.5%) * IIPC: 86.71% (±0.5%) * **Difficulty Level 5:** * PoT: 75.08% (±0.5%) * CR: 70.76% (±0.5%) * MACM: 71.10% (±0.5%) * IIPC: 79.40% (±0.5%) **5. Llama 4 Maverick** * **Trend:** Accuracy is high and relatively stable for difficulty levels 1-3, with a noticeable decrease at level 4 and a further decrease at level 5. * **Difficulty Level 1:** * PoT: 95.34% (±0.5%) * CR: 95.70% (±0.5%) * MACM: 96.06% (±0.5%) * IIPC: 96.68% (±0.5%) * **Difficulty Level 2:** * PoT: 95.68% (±0.5%) * CR: 95.68% (±0.5%) * MACM: 92.36% (±0.5%) * IIPC: 91.36% (±0.5%) * **Difficulty Level 3:** * PoT: 93.69% (±0.5%) * CR: 86.71% (±0.5%) * MACM: 87.04% (±0.5%) * IIPC: 87.71% (±0.5%) * **Difficulty Level 4:** * PoT: 74.09% (±0.5%) * CR: 72.42% (±0.5%) * MACM: 74.42% (±0.5%) * IIPC: 80.73% (±0.5%) * **Difficulty Level 5:** * No data points are visible for Difficulty Level 5 for Llama 4 Maverick. The chart appears to end at Difficulty Level 4. ### Key Observations * **General Trend:** All models exhibit a general decrease in accuracy as the difficulty level increases. * **Model Performance at Low Difficulty:** Most models achieve very high accuracy (above 90%, often above 95%) at difficulty levels 1 and 2. * **Performance Drop:** The most significant drops in accuracy occur at higher difficulty levels (4 and 5). * **Model Variability:** * **GPT-4o-mini** shows a consistent and steep decline in accuracy across all difficulty levels. * **Gemini 2.0 Flash** maintains high accuracy for the first four levels, with a notable drop at level 5. * **Mistral Small 3.2 24B** and **Gemma 3 27B** show a substantial decrease in accuracy starting from difficulty level 4. * **Llama 4 Maverick** shows a significant drop at difficulty level 4 and appears to have no data for difficulty level 5. * **Metric Performance:** Within each model and difficulty level, there are variations in performance between the four metrics (PoT, CR, MACM, IIPC). For instance, at difficulty level 1, IIPC often shows the highest accuracy, while at higher difficulty levels, the relative performance of metrics can shift. ### Interpretation The presented bar charts illustrate the performance degradation of various language models as task complexity (difficulty level) increases. This is a common and expected behavior for AI models, as more challenging tasks require more sophisticated reasoning, knowledge, and generalization capabilities, which can be harder to achieve. The data suggests that while models like Gemini 2.0 Flash and Gemma 3 27B are robust at lower difficulty levels, their performance can be significantly impacted by increased complexity. GPT-4o-mini appears to be more sensitive to difficulty increases from the outset, showing a more continuous decline. Mistral Small 3.2 24B and Gemma 3 27B demonstrate a sharp drop-off in performance at higher difficulty levels, indicating potential limitations in their ability to handle complex scenarios. The incomplete data for Llama 4 Maverick at difficulty level 5 prevents a full comparison for that model. The variations between PoT, CR, MACM, and IIPC suggest that these metrics might be evaluating different aspects of model performance or are sensitive to different types of challenges. Further investigation into what each metric represents would be necessary to fully understand these differences. Overall, the charts provide a clear visual comparison of model resilience to increasing task difficulty, highlighting areas where each model excels or struggles. This information is crucial for selecting appropriate models for tasks of varying complexity and for identifying areas for model improvement.

## Stacked Bar Charts: Model Accuracy vs. Difficulty Level ### Overview The image presents a series of stacked bar charts, each representing the accuracy of a different Large Language Model (LLM) across five levels of difficulty. The charts visually compare the performance of GPT-4o-mini, Gemini 2.0 Flash, Mistral Small 3.2 24B, Gemma 3 27B, and Llama 4 Maverick. Accuracy is represented on the y-axis (ranging from 0.0 to 1.0), and difficulty level is on the x-axis (ranging from 1 to 5). Each bar is segmented into four components, representing different evaluation metrics: PoT, CR, MACM, and IIPC. ### Components/Axes * **Y-axis:** Accuracy (Scale: 0.0 to 1.0) * **X-axis:** Difficulty Level (Levels: 1, 2, 3, 4, 5) * **Legend:** * PoT (Blue) * CR (Orange) * MACM (Red) * IIPC (Green) * **Charts:** Five separate stacked bar charts, one for each model: * GPT-4o-mini * Gemini 2.0 Flash * Mistral Small 3.2 24B * Gemma 3 27B * Llama 4 Maverick ### Detailed Analysis or Content Details **GPT-4o-mini:** * Difficulty 1: Accuracy = 93.55 (PoT), 92.11 (CR), 94.69 (MACM), 88.05 (IIPC) - Total: ~97% * Difficulty 2: Accuracy = 91.29 (PoT), 87.38 (CR), 91.03 (MACM), 73.09 (IIPC) - Total: ~86% * Difficulty 3: Accuracy = 84.05 (PoT), 81.73 (CR), 86.15 (MACM), 66.47 (IIPC) - Total: ~79% * Difficulty 4: Accuracy = 75.75 (PoT), 60.47 (CR), 43.52 (MACM), 50.17 (IIPC) - Total: ~58% * Difficulty 5: Accuracy = 56.80 (PoT), 50.17 (CR), 43.52 (MACM), 43.52 (IIPC) - Total: ~48% **Gemini 2.0 Flash:** * Difficulty 1: Accuracy = 96.06 (PoT), 95.78 (CR), 96.36 (MACM), 93.69 (IIPC) - Total: ~98% * Difficulty 2: Accuracy = 95.49 (PoT), 94.98 (CR), 95.36 (MACM), 92.61 (IIPC) - Total: ~97% * Difficulty 3: Accuracy = 93.36 (PoT), 92.10 (CR), 93.66 (MACM), 90.70 (IIPC) - Total: ~95% * Difficulty 4: Accuracy = 90.02 (PoT), 89.61 (CR), 89.36 (MACM), 85.05 (IIPC) - Total: ~88% * Difficulty 5: Accuracy = 79.63 (PoT), 75.73 (CR), 79.34 (MACM), 79.34 (IIPC) - Total: ~79% **Mistral Small 3.2 24B:** * Difficulty 1: Accuracy = 97.13 (PoT), 97.82 (CR), 94.67 (MACM), 91.32 (IIPC) - Total: ~98% * Difficulty 2: Accuracy = 96.07 (PoT), 96.02 (CR), 94.03 (MACM), 88.47 (IIPC) - Total: ~96% * Difficulty 3: Accuracy = 94.72 (PoT), 94.03 (CR), 89.87 (MACM), 80.79 (IIPC) - Total: ~92% * Difficulty 4: Accuracy = 92.47 (PoT), 91.38 (CR), 86.83 (MACM), 66.45 (IIPC) - Total: ~84% * Difficulty 5: Accuracy = 80.07 (PoT), 68.87 (CR), 66.45 (MACM), 61.79 (IIPC) - Total: ~69% **Gemma 3 27B:** * Difficulty 1: Accuracy = 97.11 (PoT), 95.34 (CR), 95.02 (MACM), 94.39 (IIPC) - Total: ~98% * Difficulty 2: Accuracy = 95.70 (PoT), 95.34 (CR), 94.39 (MACM), 91.13 (IIPC) - Total: ~96% * Difficulty 3: Accuracy = 95.02 (PoT), 94.39 (CR), 95.68 (MACM), 83.39 (IIPC) - Total: ~92% * Difficulty 4: Accuracy = 83.39 (PoT), 83.39 (CR), 83.39 (MACM), 75.06 (IIPC) - Total: ~81% * Difficulty 5: Accuracy = 79.40 (PoT), 71.41 (CR), 71.41 (MACM), 71.40 (IIPC) - Total: ~74% **Llama 4 Maverick:** * Difficulty 1: Accuracy = 95.34 (PoT), 96.06 (CR), 96.68 (MACM), 92.36 (IIPC) - Total: ~98% * Difficulty 2: Accuracy = 96.06 (PoT), 96.68 (CR), 95.38 (MACM), 87.71 (IIPC) - Total: ~96% * Difficulty 3: Accuracy = 92.96 (PoT), 92.36 (CR), 91.38 (MACM), 74.42 (IIPC) - Total: ~88% * Difficulty 4: Accuracy = 91.38 (PoT), 87.71 (CR), 86.01 (MACM), 74.42 (IIPC) - Total: ~85% * Difficulty 5: Accuracy = 72.43 (PoT), 72.43 (CR), 72.43 (MACM), 72.43 (IIPC) - Total: ~72% ### Key Observations * All models demonstrate decreasing accuracy as difficulty level increases. * Gemini 2.0 Flash and Mistral Small 3.2 24B consistently exhibit the highest accuracy across most difficulty levels. * GPT-4o-mini shows the most significant drop in accuracy with increasing difficulty, particularly at levels 4 and 5. * The contribution of each metric (PoT, CR, MACM, IIPC) to the overall accuracy varies across models and difficulty levels. * IIPC generally has the lowest contribution to overall accuracy, and its decline with difficulty is often more pronounced. ### Interpretation The data suggests a clear correlation between model performance and task difficulty. More capable models (Gemini 2.0 Flash, Mistral Small 3.2 24B) maintain higher accuracy levels even as the difficulty increases. The stacked bar charts reveal that the different evaluation metrics contribute differently to the overall accuracy score. The decline in IIPC accuracy across all models with increasing difficulty suggests that this metric is particularly sensitive to task complexity. The significant drop in GPT-4o-mini's accuracy at higher difficulty levels indicates a potential limitation in its ability to generalize to more challenging tasks. This visualization is valuable for comparing the strengths and weaknesses of different LLMs and understanding how their performance varies across a range of difficulty levels. The data could be used to inform model selection for specific applications based on the expected task complexity.

## [Grouped Bar Charts]: AI Model Performance Across Difficulty Levels (Four Metrics) ### Overview The image contains five grouped bar charts, each representing a different AI model (GPT-4o-mini, Gemini 2.0 Flash, Mistral Small 3.2 24B, Gemma 3 27B, Llama 4 Maverick). Each chart plots **Accuracy** (y-axis, 0.0–1.0) against **Difficulty Level** (x-axis, 1–5, categorical). Four metrics are compared: *PoT* (blue), *CR* (orange), *MACM* (green), and *IIPC* (red), as indicated by the legend at the bottom. ### Components/Axes - **X-axis**: *Difficulty Level* (1, 2, 3, 4, 5) – represents increasing task complexity. - **Y-axis**: *Accuracy* (0.0 to 1.0) – continuous scale measuring performance. - **Legend**: Four metrics with color coding: - PoT (blue) - CR (orange) - MACM (green) - IIPC (red) - **Subplots**: Five subplots, each titled with the model name (e.g., “GPT-4o-mini,” “Gemini 2.0 Flash”). ### Detailed Analysis (Per Model) #### 1. GPT-4o-mini (Top-Left) - **Difficulty 1**: PoT ≈ 0.95, CR ≈ 0.91, MACM ≈ 0.91, IIPC ≈ 0.94 - **Difficulty 2**: PoT ≈ 0.91, CR ≈ 0.87, MACM ≈ 0.87, IIPC ≈ 0.91 - **Difficulty 3**: PoT ≈ 0.84, CR ≈ 0.81, MACM ≈ 0.77, IIPC ≈ 0.86 - **Difficulty 4**: PoT ≈ 0.77, CR ≈ 0.73, MACM ≈ 0.66, IIPC ≈ 0.75 - **Difficulty 5**: PoT ≈ 0.60, CR ≈ 0.50, MACM ≈ 0.43, IIPC ≈ 0.58 - **Trend**: All metrics decline with difficulty. MACM shows the steepest drop (from ~0.91 to ~0.43), while IIPC remains relatively higher at higher difficulties. #### 2. Gemini 2.0 Flash (Top-Right) - **Difficulty 1**: PoT ≈ 0.96, CR ≈ 0.95, MACM ≈ 0.94, IIPC ≈ 0.96 - **Difficulty 2**: PoT ≈ 0.96, CR ≈ 0.95, MACM ≈ 0.95, IIPC ≈ 0.97 - **Difficulty 3**: PoT ≈ 0.93, CR ≈ 0.91, MACM ≈ 0.91, IIPC ≈ 0.95 - **Difficulty 4**: PoT ≈ 0.90, CR ≈ 0.89, MACM ≈ 0.89, IIPC ≈ 0.93 - **Difficulty 5**: PoT ≈ 0.83, CR ≈ 0.79, MACM ≈ 0.77, IIPC ≈ 0.87 - **Trend**: Gradual decline with difficulty. IIPC consistently outperforms others (e.g., Difficulty 5: IIPC ≈ 0.87 vs. PoT ≈ 0.83). #### 3. Mistral Small 3.2 24B (Middle-Left) - **Difficulty 1**: PoT ≈ 0.97, CR ≈ 0.92, MACM ≈ 0.92, IIPC ≈ 0.96 - **Difficulty 2**: PoT ≈ 0.94, CR ≈ 0.91, MACM ≈ 0.90, IIPC ≈ 0.94 - **Difficulty 3**: PoT ≈ 0.94, CR ≈ 0.88, MACM ≈ 0.83, IIPC ≈ 0.90 - **Difficulty 4**: PoT ≈ 0.87, CR ≈ 0.80, MACM ≈ 0.76, IIPC ≈ 0.83 - **Difficulty 5**: PoT ≈ 0.76, CR ≈ 0.66, MACM ≈ 0.63, IIPC ≈ 0.80 - **Trend**: All metrics decrease with difficulty. MACM has a notable drop (from ~0.92 to ~0.63), while IIPC remains competitive (e.g., Difficulty 5: IIPC ≈ 0.80 vs. PoT ≈ 0.76). #### 4. Gemma 3 27B (Middle-Right) - **Difficulty 1**: PoT ≈ 0.97, CR ≈ 0.95, MACM ≈ 0.95, IIPC ≈ 0.95 - **Difficulty 2**: PoT ≈ 0.96, CR ≈ 0.95, MACM ≈ 0.94, IIPC ≈ 0.96 - **Difficulty 3**: PoT ≈ 0.93, CR ≈ 0.91, MACM ≈ 0.90, IIPC ≈ 0.95 - **Difficulty 4**: PoT ≈ 0.89, CR ≈ 0.83, MACM ≈ 0.83, IIPC ≈ 0.87 - **Difficulty 5**: PoT ≈ 0.75, CR ≈ 0.70, MACM ≈ 0.71, IIPC ≈ 0.79 - **Trend**: Gradual decline. IIPC is consistently high (e.g., Difficulty 5: IIPC ≈ 0.79 vs. PoT ≈ 0.75). #### 5. Llama 4 Maverick (Bottom) - **Difficulty 1**: PoT ≈ 0.95, CR ≈ 0.95, MACM ≈ 0.95, IIPC ≈ 0.98 - **Difficulty 2**: PoT ≈ 0.96, CR ≈ 0.95, MACM ≈ 0.95, IIPC ≈ 0.96 - **Difficulty 3**: PoT ≈ 0.92, CR ≈ 0.91, MACM ≈ 0.92, IIPC ≈ 0.93 - **Difficulty 4**: PoT ≈ 0.89, CR ≈ 0.87, MACM ≈ 0.87, IIPC ≈ 0.89 - **Difficulty 5**: PoT ≈ 0.74, CR ≈ 0.74, MACM ≈ 0.72, IIPC ≈ 0.80 - **Trend**: All metrics decline with difficulty. IIPC is the highest at Difficulty 5 (≈0.80), while MACM is the lowest (≈0.72). ### Key Observations - **Metric Robustness**: *IIPC* (red) consistently outperforms or matches other metrics across most models and difficulty levels, especially at higher difficulties. *MACM* (green) often shows the steepest decline with increasing difficulty. - **Model Resilience**: Gemini 2.0 Flash and Llama 4 Maverick maintain relatively high accuracy across difficulties, while GPT-4o-mini shows a more pronounced drop at higher difficulties. - **Difficulty Impact**: All models exhibit a clear trend of decreasing accuracy with increasing difficulty, indicating task complexity negatively impacts performance across all metrics and models. ### Interpretation The data suggests **task difficulty is a critical factor** in AI model performance, with accuracy declining as difficulty increases. The *IIPC* metric appears more robust to complexity, making it a reliable measure for challenging tasks. Models like Gemini 2.0 Flash and Llama 4 Maverick demonstrate better resilience, suggesting they may be better suited for complex problems. The consistent decline in *MACM* across models indicates it is particularly sensitive to task complexity, which could help identify models that struggle with harder tasks. This analysis highlights the importance of evaluating AI models across multiple metrics and difficulty levels to understand their strengths and limitations in real-world scenarios.

## Bar Chart: Model Accuracy Across Difficulty Levels ### Overview The chart compares the accuracy of four AI models (GPT-4o-mini, Gemini 2.0 Flash, Mistral Small 3.2 24B, Llama 4 Maverick) across five difficulty levels (1–5). Four evaluation methods are tested: PoT (blue), CR (orange), MACM (green), and IIPC (red). Accuracy is measured on a 0–1.0 scale. ### Components/Axes - **X-axis**: Difficulty Level (1–5, categorical) - **Y-axis**: Accuracy (0–1.0, linear scale) - **Legend**: Located at the bottom, mapping colors to methods: - Blue = PoT - Orange = CR - Green = MACM - Red = IIPC - **Models**: Grouped by model name (top to bottom: GPT-4o-mini, Gemini 2.0 Flash, Mistral Small 3.2 24B, Llama 4 Maverick) ### Detailed Analysis #### GPT-4o-mini - **Difficulty 1**: - PoT: 93.55 (blue) - CR: 91.40 (orange) - MACM: 92.11 (green) - IIPC: 94.27 (red) - **Difficulty 2**: - PoT: 91.69 - CR: 87.38 - MACM: 87.38 - IIPC: 91.03 - **Difficulty 3**: - PoT: 84.05 - CR: 81.73 - MACM: 75.75 - IIPC: 86.05 - **Difficulty 4**: - PoT: 77.08 - CR: 73.09 - MACM: 66.00 - IIPC: 75.75 - **Difficulty 5**: - PoT: 60.47 - CR: 50.17 - MACM: 43.52 - IIPC: 58.80 #### Gemini 2.0 Flash - **Difficulty 1**: - PoT: 96.06 - CR: 95.70 - MACM: 94.98 - IIPC: 96.77 - **Difficulty 2**: - PoT: 98.01 - CR: 95.35 - MACM: 96.01 - IIPC: 97.01 - **Difficulty 3**: - PoT: 93.36 - CR: 91.03 - MACM: 92.67 - IIPC: 96.01 - **Difficulty 4**: - PoT: 90.70 - CR: 89.04 - MACM: 90.03 - IIPC: 93.69 - **Difficulty 5**: - PoT: 85.05 - CR: 79.73 - MACM: 77.41 - IIPC: 87.38 #### Mistral Small 3.2 24B - **Difficulty 1**: - PoT: 97.13 - CR: 92.11 - MACM: 92.47 - IIPC: 96.77 - **Difficulty 2**: - PoT: 94.02 - CR: 91.36 - MACM: 90.70 - IIPC: 96.01 - **Difficulty 3**: - PoT: 94.02 - CR: 88.37 - MACM: 83.72 - IIPC: 93.02 - **Difficulty 4**: - PoT: 87.38 - CR: 80.40 - MACM: 80.73 - IIPC: 88.70 - **Difficulty 5**: - PoT: 76.08 - CR: 66.45 - MACM: 63.79 - IIPC: 80.07 #### Llama 4 Maverick - **Difficulty 1**: - PoT: 95.34 - CR: 95.70 - MACM: 96.06 - IIPC: 96.68 - **Difficulty 2**: - PoT: 96.68 - CR: 95.68 - MACM: 95.68 - IIPC: 96.68 - **Difficulty 3**: - PoT: 92.36 - CR: 91.36 - MACM: 92.03 - IIPC: 93.69 - **Difficulty 4**: - PoT: 86.71 - CR: 87.04 - MACM: 87.71 - IIPC: 89.37 - **Difficulty 5**: - PoT: 74.09 - CR: 74.42 - MACM: 72.43 - IIPC: 80.73 ### Key Observations 1. **Accuracy Degradation**: All models show declining accuracy with increasing difficulty, but Gemini 2.0 Flash and Llama 4 Maverick maintain higher performance at Difficulty 5 compared to GPT-4o-mini and Mistral. 2. **Method Performance**: - **PoT** (blue) generally underperforms other methods across most models and difficulties. - **IIPC** (red) often achieves the highest accuracy, particularly for Gemini 2.0 Flash and Llama 4 Maverick. - **MACM** (green) shows the steepest drop in accuracy at higher difficulties for GPT-4o-mini and Mistral. 3. **Outliers**: - GPT-4o-mini’s MACM method drops to 43.52 at Difficulty 5, the lowest observed value. - Llama 4 Maverick’s IIPC method maintains 80.73 accuracy at Difficulty 5, the highest among all models at this level. ### Interpretation The data suggests that **IIPC** is the most robust method across models, maintaining higher accuracy even at extreme difficulty levels. **PoT** consistently underperforms, indicating potential limitations in its approach. Models like **Gemini 2.0 Flash** and **Llama 4 Maverick** demonstrate superior scalability to higher difficulties, possibly due to architectural advantages or training data quality. The divergence in MACM performance highlights sensitivity to task complexity, suggesting it may rely on specific patterns that degrade under challenging conditions. These findings underscore the importance of method selection based on expected task difficulty in real-world applications.