## Chart: Performance Comparison of X-EcoMLA-8B vs Llama3.1-8B
### Overview
This image is a dual-axis line chart comparing the performance metrics of two Large Language Models (LLMs): **X-EcoMLA-8B** and **Llama3.1-8B**. The chart plots **Throughput (tokens/sec)** on the left Y-axis (blue) and **Peak Memory Usage (GB)** on the right Y-axis (red) against a logarithmic **Batch Size** on the X-axis.
### Components/Axes
* **X-Axis (Bottom):** "Batch Size". Logarithmic scale with markers at 8, 16, 32, 64, 128, 256, 512, and 1024.
* **Left Y-Axis (Blue):** "Throughput (tokens/sec)". Scale ranges from 0 to 5000+.
* **Right Y-Axis (Red):** "Peak Memory Usage (GB)". Scale ranges from 0 to 140+.
* **Legend (Bottom-Right):**
* **Blue solid line with circles:** X-EcoMLA-8B Throughput
* **Cyan solid line with squares:** Llama3.1-8B Throughput
* **Red dashed line with triangles (pointing up):** X-EcoMLA-8B Memory
* **Orange dashed line with triangles (pointing down):** Llama3.1-8B Memory
### Detailed Analysis
#### Data Series Trends
1. **X-EcoMLA-8B Throughput (Blue Solid Line):** Slopes upward consistently. The growth is steep between batch sizes 8 and 128, then begins to plateau slightly as it approaches batch size 1024.
2. **Llama3.1-8B Throughput (Cyan Solid Line):** Slopes upward, but the growth rate diminishes significantly after batch size 32, effectively flattening out by batch size 128.
3. **X-EcoMLA-8B Memory (Red Dashed Line):** Slopes upward. The growth is relatively linear and gradual across the entire range of batch sizes (8 to 1024).
4. **Llama3.1-8B Memory (Orange Dashed Line):** Slopes upward very steeply. The line exits the top of the chart area shortly after batch size 64.
#### Approximate Data Points
| Batch Size | X-EcoMLA-8B Throughput (tokens/s) | Llama3.1-8B Throughput (tokens/s) | X-EcoMLA-8B Memory (GB) | Llama3.1-8B Memory (GB) |
| :--- | :--- | :--- | :--- | :--- |
| **8** | ~700 | ~650 | ~18 | ~20 |
| **16** | ~1300 | ~900 | ~20 | ~35 |
| **32** | ~2200 | ~1600 | ~22 | ~60 |
| **64** | ~3200 | ~2000 | ~25 | ~80 |
| **128** | ~3900 | ~2150 | ~30 | ~145+ |
| **256** | ~4600 | N/A | ~40 | N/A |
| **512** | ~5050 | N/A | ~65 | N/A |
| **1024** | ~5250 | N/A | ~115 | N/A |
*(Note: "N/A" indicates data points not plotted for that series.)*
### Key Observations
* **Throughput Divergence:** X-EcoMLA-8B maintains a higher throughput than Llama3.1-8B at every measured batch size. While Llama3.1-8B throughput plateaus around 2150 tokens/sec at batch size 128, X-EcoMLA-8B continues to scale up to over 5000 tokens/sec at batch size 1024.
* **Memory Efficiency:** The most striking difference is in memory usage. Llama3.1-8B consumes memory at a much higher rate, hitting ~80GB at batch size 64, whereas X-EcoMLA-8B uses only ~25GB at the same batch size.
* **Scalability:** X-EcoMLA-8B demonstrates significantly better scalability, allowing for much larger batch sizes (up to 1024) within reasonable memory constraints, whereas Llama3.1-8B appears to hit a "memory wall" very early.
### Interpretation
The data suggests that **X-EcoMLA-8B** is highly optimized for high-throughput, high-batch-size inference scenarios. The "Eco" in its name likely refers to this superior memory efficiency.
Conversely, **Llama3.1-8B** appears to be significantly less efficient in terms of memory overhead when scaling batch sizes. The rapid, steep rise in the orange dashed line (Llama3.1-8B Memory) indicates that it cannot support large batch sizes on standard hardware configurations, limiting its practical throughput ceiling compared to the X-EcoMLA-8B model. This chart serves as a performance benchmark demonstrating that X-EcoMLA-8B is the superior choice for high-volume, high-throughput deployment environments.
