diff --git a/docs/design/prefix_caching.md b/docs/design/prefix_caching.md
index 6f2eb3062..0f3100c9b 100644
--- a/docs/design/prefix_caching.md
+++ b/docs/design/prefix_caching.md
@@ -22,8 +22,13 @@ In the example above, the KV cache in the first block can be uniquely identified
     We only cache full blocks.
 
 !!! note "Note 2"
-    The above hash key structure is not 100% collision free. Theoretically it’s still possible for the different prefix tokens to have the same hash value. To avoid any hash collisions **in a multi-tenant setup, we use SHA256** as hash function instead of the builtin hash.
-    SHA256 is supported since vLLM v0.8.3 and the default since v0.10.2. It comes with a negligible performance impact of about 75ns per token (<4ms for 50k tokens of context).
+    In previous versions, the hash key was not guaranteed to be collision-free. As of v0.11, the default hashing algorithm is `sha256`, which addresses collision risks.
+
+    For `vllm serve`, you can control the hashing algorithm via `--prefix-caching-hash-algo`:
+    - `sha256` (default): Uses Python's `pickle` for serialization. Hashes may not be reproducible across different Python or vLLM versions.
+    - `sha256_cbor`: Uses `cbor2` for serialization, providing a reproducible, cross-language compatible hash. This is recommended for deterministic caching across environments.
+    - `xxhash`: `Uses Pickle serialization with xxHash (128-bit) for faster, non-cryptographic hashing. Requires the optional `xxhash` package. IMPORTANT: Use of a hashing algorithm that is not considered cryptographically secure theoretically increases the risk of hash collisions, which can cause undefined behavior or even leak private information in multi-tenant environments. Even if collisions are still very unlikely, it is important to consider your security risk tolerance against the performance benefits before turning this on.
+    - `xxhash_cbor` combines canonical CBOR serialization with xxHash for reproducible hashing. Requires the optional `xxhash` package.    
 
 **A hashing example with multi-modality inputs**  
 In this example, we illustrate how prefix caching works with multi-modality inputs (e.g., images). Assuming we have a request with the following messages: