diff --git a/docs/source/blogs/tech_blog/blog1_Pushing_Latency_Boundaries_Optimizing_DeepSeek-R1_Performance_on_NVIDIA_B200_GPUs.md b/docs/source/blogs/tech_blog/blog1_Pushing_Latency_Boundaries_Optimizing_DeepSeek-R1_Performance_on_NVIDIA_B200_GPUs.md
index 6a19c021e6aa..098db32083ad 100644
--- a/docs/source/blogs/tech_blog/blog1_Pushing_Latency_Boundaries_Optimizing_DeepSeek-R1_Performance_on_NVIDIA_B200_GPUs.md
+++ b/docs/source/blogs/tech_blog/blog1_Pushing_Latency_Boundaries_Optimizing_DeepSeek-R1_Performance_on_NVIDIA_B200_GPUs.md
@@ -136,7 +136,7 @@ The modules in the diagram are:
 | Optimize CUTLASS Flow: Sparse Experts as GEMMs            |   249    | The code is not open-source yet due to the dependency with internal base environment and we are planning to make it decoupled from internal base environment thus to be able to open-source in the future.|
 | Introduce EP4TP2 for better workload balance              |   253    | Use `--tp 8 --ep 4` when benchmarking                                                                                                                       |
 | Introduce moe_backend=TRTLLM, EP2TP4 for better balance   |   299    | [PR #4280](https://github.com/NVIDIA/TensorRT-LLM/pull/4280)                                                                                          |
-| Optimize Fuse_A_GEMM and Router_GEMM                      |   340    | WIP: [PR #4115](https://github.com/NVIDIA/TensorRT-LLM/pull/4115)                                                                                          |
+| Optimize Fuse_A_GEMM and Router_GEMM                      |   340    | WIP)                                                                                          |
 | Relax Acceptance                                          |   **368**    | [deepseek_v3#multi-token-prediction-mtp](https://github.com/NVIDIA/TensorRT-LLM/tree/main/examples/models/core/deepseek_v3#multi-token-prediction-mtp)     |
 
 ### System Level optimizations