Update README.md

README.md

@@ -334,6 +334,37 @@ The following performance benchmarks were conducted with [vLLM](https://docs.vll
     </tr>
   </thead>
   <tbody style="text-align: center">
+       <tr>
+      <th rowspan="3" valign="top">A6000x1</th>
+      <th>Qwen/Qwen2.5-VL-7B-Instruct</th>
+      <td></td>
+      <td>4.9</td>
+      <td>912</td>
+      <td>3.2</td>
+      <td>1386</td>
+      <td>3.1</td>
+      <td>1431</td>
+    </tr>
+    <tr>
+      <th>neuralmagic/Qwen2.5-VL-7B-Instruct-quantized.w8a8</th>
+      <td>1.50</td>
+      <td>3.6</td>
+      <td>1248</td>
+      <td>2.1</td>
+      <td>2163</td>
+      <td>2.0</td>
+      <td>2237</td>
+    </tr>
+    <tr>
+      <th>neuralmagic/Qwen2.5-VL-7B-Instruct-quantized.w4a16</th>
+      <td>2.05</td>
+      <td>3.3</td>
+      <td>1351</td>
+      <td>1.4</td>
+      <td>3252</td>
+      <td>1.4</td>
+      <td>3321</td>
+    </tr>
     <tr>
       <th rowspan="3" valign="top">A100x1</th>
       <th>Qwen/Qwen2.5-VL-7B-Instruct</th>
@@ -398,12 +429,11 @@ The following performance benchmarks were conducted with [vLLM](https://docs.vll
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   </tbody>
 </table>
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+ 
 **Use case profiles: Image Size (WxH) / prompt tokens / generation tokens
 
 **QPD: Queries per dollar, based on on-demand cost at [Lambda Labs](https://lambdalabs.com/service/gpu-cloud) (observed on 2/18/2025).
 
-
 ### Multi-stream asynchronous performance (measured with vLLM version 0.7.2)
 
 <table border="1" class="dataframe">
@@ -429,9 +459,40 @@ The following performance benchmarks were conducted with [vLLM](https://docs.vll
     </tr>
   </thead>
   <tbody style="text-align: center">
+    <tr>
+      <th rowspan="3" valign="top">A6000x1</th>
+      <th>Qwen/Qwen2.5-VL-7B-Instruct</th>
+      <td></td>
+      <td>0.4</td>
+      <td>1837</td>
+      <td>1.5</td>
+      <td>6846</td>
+      <td>1.7</td>
+      <td>7638</td>
+    </tr>
+    <tr>
+      <th>neuralmagic/Qwen2.5-VL-7B-Instruct-quantized.w8a8</th>
+      <td>1.41</td>
+      <td>0.5</td>
+      <td>2297</td>
+      <td>2.3</td>
+      <td>10137</td>
+      <td>2.5</td>
+      <td>11472</td>
+    </tr>
+    <tr>
+      <th>neuralmagic/Qwen2.5-VL-7B-Instruct-quantized.w4a16</th>
+      <td>1.60</td>
+      <td>0.4</td>
+      <td>1828</td>
+      <td>2.7</td>
+      <td>12254</td>
+      <td>3.4</td>
+      <td>15477</td>
+    </tr>
      <tr>
       <th rowspan="3" valign="top">A100x1</th>
-      <th>Qwen/Qwen2.5-VL-7B-Instruct-quantized.</th>
+      <th>Qwen/Qwen2.5-VL-7B-Instruct</th>
       <td></td>
       <td>0.7</td>
       <td>1347</td>