# Technical Document Extraction: Performance Analysis Chart ## 1. Component Isolation * **Header:** None present. * **Main Chart Area:** A line graph with markers plotted on a white grid background. It features four distinct data series and a horizontal reference line. * **Legend:** Located in the top-right quadrant of the chart area. * **Axes:** * **Y-Axis (Vertical):** Labeled "Tokens per Second". Scale ranges from 20 to 55 with increments of 5. * **X-Axis (Horizontal):** Labeled "Gamma". Scale ranges from 0 to 15 with increments of 2. --- ## 2. Legend and Data Series Identification The legend is positioned at approximately `[x=0.85, y=0.15]` relative to the top-right corner. | Series Label | Line Color | Marker Style | Visual Trend Description | | :--- | :--- | :--- | :--- | | **Llama-68M** | Blue | Solid circle | Increases sharply to a peak at Gamma=3, then follows a steady, gradual decline. Remains the highest performing series throughout. | | **Llama-160M** | Orange | Solid circle | Increases to a peak at Gamma=2, then declines steadily. It generally sits between the Vicuna-1B and Llama-1B lines after Gamma=5. | | **Llama-1B** | Green | Solid circle | Increases to a peak at Gamma=2, then declines steadily. This is the lowest performing series across all Gamma values. | | **Vicuna-1B** | Red | Solid circle | Increases to a peak at Gamma=2, then declines. It maintains a higher throughput than Llama-160M and Llama-1B for Gamma values > 5. | --- ## 3. Data Extraction ### Reference Line * **Type:** Horizontal dashed grey line. * **Value:** Approximately **34.5 Tokens per Second**. ### Numerical Data Points (Estimated from Grid) Values are extracted by cross-referencing marker positions against the Y-axis (Tokens per Second) and X-axis (Gamma). | Gamma | Llama-68M (Blue) | Llama-160M (Orange) | Llama-1B (Green) | Vicuna-1B (Red) | | :--- | :--- | :--- | :--- | :--- | | **1** | 47.5 | 44.2 | 39.4 | 43.4 | | **2** | 51.5 | 45.4 | 40.5 | 46.1 | | **3** | 54.0 | 44.9 | 39.1 | 45.2 | | **4** | 53.1 | 42.9 | 37.1 | 41.9 | | **5** | 52.1 | 39.9 | 34.5 | 40.2 | | **6** | 51.7 | 36.4 | 31.8 | 38.1 | | **7** | 49.0 | 34.0 | 29.2 | 37.9 | | **8** | 48.2 | 32.1 | 27.7 | 34.9 | | **9** | 46.5 | 29.3 | 27.1 | 33.3 | | **10** | 44.2 | 28.5 | 24.6 | 31.4 | | **11** | 43.6 | 27.2 | 23.8 | 30.1 | | **12** | 42.3 | 25.7 | 21.8 | 29.3 | | **13** | 40.7 | 25.0 | 20.7 | 27.9 | | **14** | 39.5 | 22.7 | 19.9 | 26.3 | | **15** | 38.1 | 22.2 | 18.7 | 25.0 | --- ## 4. Key Trends and Observations 1. **Optimal Gamma:** All models exhibit an initial performance increase, peaking at low Gamma values. Llama-68M peaks at **Gamma=3**, while the other three models (Llama-160M, Llama-1B, Vicuna-1B) peak earlier at **Gamma=2**. 2. **Inverse Correlation:** Beyond the peak (Gamma > 3), there is a clear inverse correlation between the Gamma value and Tokens per Second; as Gamma increases, throughput decreases for all models. 3. **Model Size vs. Speed:** There is a general trend where smaller models (Llama-68M) perform significantly faster than larger models (Llama-1B). However, Vicuna-1B (Red) outperforms the smaller Llama-160M (Orange) for Gamma values of 7 and above. 4. **Performance Threshold:** The Llama-68M model remains above the ~34.5 tokens/sec reference line for the entire tested range. In contrast, Llama-1B falls below this threshold after Gamma=5.

**Technical Document Extraction: Line Chart Analysis** **Chart Type**: Line chart with four data series. **Axes**: - **X-axis (Horizontal)**: Labeled "Gamma" with integer markers from 0 to 15. - **Y-axis (Vertical)**: Labeled "Tokens per Second" with integer markers from 20 to 55. A dashed horizontal line at **35** is present. **Legend**: - **Blue line**: Llama-68M - **Orange line**: Llama-160M - **Green line**: Llama-1B - **Red line**: Vicuna-1B **Key Trends**: 1. **Llama-68M (Blue)**: - Starts at ~47 tokens/sec at Gamma=0. - Peaks at ~54 tokens/sec at Gamma=3. - Gradually declines to ~38 tokens/sec at Gamma=15. - Maintains the highest performance across all Gamma values. 2. **Llama-160M (Orange)**: - Begins at ~44 tokens/sec at Gamma=0. - Drops sharply to ~35 tokens/sec by Gamma=5. - Continues declining to ~22 tokens/sec at Gamma=15. - Crosses below Llama-1B at Gamma=4. 3. **Llama-1B (Green)**: - Starts at ~39 tokens/sec at Gamma=0. - Declines steadily to ~20 tokens/sec by Gamma=10. - Reaches ~18 tokens/sec at Gamma=15. - Crosses below the 35-token threshold at Gamma=5. 4. **Vicuna-1B (Red)**: - Begins at ~43 tokens/sec at Gamma=0. - Drops to ~35 tokens/sec by Gamma=5. - Continues declining to ~25 tokens/sec at Gamma=15. - Crosses below Llama-160M at Gamma=3. **Critical Observations**: - **Performance Threshold**: The dashed line at 35 tokens/sec acts as a performance benchmark. All models except Llama-68M fall below this threshold by Gamma=8. - **Model Efficiency**: Llama-68M demonstrates superior scalability, retaining higher token generation rates across increasing Gamma values compared to other models. - **Divergence Points**: - Llama-160M and Vicuna-1B intersect near Gamma=3 (~42 tokens/sec). - Llama-1B falls below Llama-160M at Gamma=4 (~38 tokens/sec). **Data Points (Selected)**: - **Llama-68M**: - Gamma=0: 47 - Gamma=3: 54 - Gamma=15: 38 - **Llama-160M**: - Gamma=0: 44 - Gamma=5: 35 - Gamma=15: 22 - **Llama-1B**: - Gamma=0: 39 - Gamma=5: 35 - Gamma=15: 18 - **Vicuna-1B**: - Gamma=0: 43 - Gamma=5: 35 - Gamma=15: 25 **Conclusion**: The chart illustrates a trade-off between model size (Llama variants) and performance efficiency (Tokens per Second) as Gamma increases. Llama-68M maintains dominance, while smaller models (Llama-160M, Llama-1B) and Vicuna-1B exhibit steeper declines, highlighting diminishing returns at higher Gamma values.