Update README.md

README.md

@@ -532,6 +532,72 @@ outputs = llm.chat(messages, sampling_params=sampling_params)
 print(outputs[0].outputs[0].text)
 ```
 
+## Accuracy 
+<table>
+  <thead>
+    <tr>
+      <th>Category</th>
+      <th>Metric</th>
+      <th>neuralmagic/Pixtral-Large-Instruct-2411-hf</th>
+      <th>neuralmagic/Pixtral-Large-Instruct-2411-hf-FP8-dynamic</th>
+      <th>Recovery (%)</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td rowspan="6"><b>Vision</b></td>
+      <td>MMMU (val, CoT)<br><i>explicit_prompt_relaxed_correctness</i></td>
+      <td>63.56</td>
+      <td>63.44</td>
+      <td>99.81%</td>
+    </tr>
+    <tr>
+      <td>VQAv2 (val)<br><i>vqa_match</i></td>
+      <td>79.03</td>
+      <td>79.06</td>
+      <td>100.04%</td>
+    </tr>
+    <tr>
+      <td>DocVQA (val)<br><i>anls</i></td>
+      <td>89.55</td>
+      <td>89.63</td>
+      <td>100.09%</td>
+    </tr>
+    <tr>
+      <td>ChartQA (test, CoT)<br><i>anywhere_in_answer_relaxed_correctness</i></td>
+      <td>82.24</td>
+      <td>82.80</td>
+      <td>100.68%</td>
+    </tr>
+    <tr>
+      <td>Mathvista (testmini, CoT)<br><i>explicit_prompt_relaxed_correctness</i></td>
+      <td>67.3</td>
+      <td>66.50</td>
+      <td>98.81%</td>
+    </tr>
+    <tr>
+      <td><b>Average Score</b></td>
+      <td><b>76.34</b></td>
+      <td><b>76.29</b></td>
+      <td><b>99.93%</b></td>
+    </tr>
+    <tr>
+      <td rowspan="2"><b>Text</b></td>
+      <td>MGSM (CoT)</td>
+      <td>76.05</td>
+      <td>75.58</td>
+      <td>99.38%</td>
+    </tr>
+    <tr>
+      <td>MMLU (5-shot)</td>
+      <td>82.8</td>
+      <td>82.74</td>
+      <td>99.93%</td>
+    </tr>
+  </tbody>
+</table>
+
+
 ## Inference Performance