Update 2025-09-18-dynamo-lmcache.md

Author: junchenj

_posts/2025-09-18-dynamo-lmcache.md

@@ -7,6 +7,9 @@ author: NVIDIA Dynamo team, LMCache team
 
 We're thrilled to announce that [**Nvidia Dynamo**](https://github.com/ai-dynamo/dynamo) **has integrated [LMCache](https://github.com/LMCache/LMCache) as a [KV caching layer solution](https://docs.nvidia.com/dynamo/latest/components/backends/vllm/LMCache_Integration.html)**. This is a big milestone: Dynamo gets a battle-tested caching solution, and LMCache becomes part of a data center-scale inference platform used by many developers worldwide to deploy AI at scale.
 
+<img width="1239" height="228" alt="image" src="https://github.com/user-attachments/assets/303891b9-f5ac-4757-b300-29955a52639a" />
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 For comprehensive details about Dynamo's KV cache optimization capabilities, see the **[NVIDIA Developer Blog post on reducing KV cache bottlenecks](https://developer.nvidia.com/blog/how-to-reduce-kv-cache-bottlenecks-with-nvidia-dynamo/)**.
 
 ## **Why KV Caching Matters**
@@ -54,4 +57,4 @@ Together, with the Dynamo team, we’re laying the foundation for a **more effic
 
 **Acknowledgements**
 
-Special thanks to Vikram Mailthody, Harry Kim, Ashutosh Malegaonkar, Suman Taitraju, Richard Huo, Omri Kahalon, Vishwanath Venkatesan, Adit Ranadive, Pen Chung Li, John Kim, and David Edelsohn, in close collaboration with LMCache contributors from TensorMesh. 
+Special thanks to Vikram Mailthody, Harry Kim, Ashutosh Malegaonkar, Suman Taitraju, Richard Huo, Omri Kahalon, Vishwanath Venkatesan, Adit Ranadive, Pen Chung Li, John Kim, and David Edelsohn, in close collaboration with LMCache contributors from TensorMesh.