Refresh ascend link (#87)

Signed-off-by: wangxiyuan <[email protected]>

Author: wangxiyuan

_posts/2025-09-29-deepseek-v3-2.md

@@ -102,7 +102,7 @@ We are also excited to announce out-of-the-box Blackwell support for this model.
 We are barely touching the surface of the optimization for DSA and related sparse attention in vLLM. In the coming weeks: 
 
 * We plan to expand the architectures supported beyond Hopper and Blackwell.
-* We will expand the support to other hardwares such as AMD and TPU. With vLLM's extensible systems, developers can add support for models directly. For example, [vllm-ascend](https://github.com/vllm-project/vllm-ascend/tree/v0.9.1-dev/examples/deepseek.md) and [vllm-mlu](https://github.com/Cambricon/vllm-mlu) already support DeepSeek V3.2! 
+* We will expand the support to other hardwares such as AMD and TPU. With vLLM's extensible systems, developers can add support for models directly. For example, [vllm-ascend](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.11.0rc0) and [vllm-mlu](https://github.com/Cambricon/vllm-mlu) already support DeepSeek V3.2!
 * We continuously test large-scale wide EP serving and disaggregation.
 * You will soon be able to run an end-to-end RL loop with this model.
 * We will explore the "masked MHA mode for short sequence prefilling" from DeepSeek.