✨ [llm][npu][quant] Add W8A8 MXFP8 quantization for Qwen3 MoE on Ascend NPU (#30768)

Co-authored-by: Артем Савкин <58187114+OrangeRedeng@users.noreply.github.com>
Co-authored-by: ronnie_zheng <zl19940307@163.com>

docs_new/docs/advanced_features/quantization.mdx

@@ -53,8 +53,8 @@ The following table summarizes quantization method support across NVIDIA and AMD
       <td><code>mxfp8</code></td>
       <td>No</td>
       <td>No</td>
-      <td>Yes (A5 for Diffusion and LLM Dense Linear)</td>
-      <td>Ascend NPU only; online MXFP8 quantization for Diffusion models (e.g., Wan2.2) and LLM Dense Linear on A5 series; uses CANN <code>npu_dynamic_mx_quant</code> / <code>npu_quant_matmul</code> kernels</td>
+      <td>Yes (A5 for Diffusion, LLM Dense Linear and LLM MoE)</td>
+      <td>Ascend NPU only; online + offline MXFP8 for Diffusion models (e.g., Wan2.2), LLM Dense Linear, and LLM MoE (FusedMoE, e.g. Qwen3-30B-A3B) on A5 series; uses CANN <code>npu_dynamic_mx_quant</code> / <code>npu_quant_matmul</code> (dense) and <code>npu_grouped_matmul_swiglu_quant_v2</code> / <code>npu_grouped_matmul</code> (MoE) kernels</td>
     </tr>
     <tr>
       <td><code>mxfp_w4a8</code></td>