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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 11, 22:30 UTC

prefix caching design doc sha256 now default (#29261)

Signed-off-by: redwrasse <mail@redwrasse.io>

redwrasse committed Dec 5, 2025 at 23:39 UTC 6476382384d3560367e30732995e2456ec569c5d
1 file changed +2 -2
docs/design/prefix_caching.md
+2 -2
@@ -22,8 +22,8 @@ In the example above, the KV cache in the first block can be uniquely identified
22 We only cache full blocks.
23
24 !!! note "Note 2"
25 - 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 advise to use SHA256** as hash function instead of the default builtin hash.
26 - SHA256 is supported since vLLM v0.8.3 and must be enabled with a command line argument. It comes with a performance impact of about 100-200ns per token (~6ms for 50k tokens of context).
25 + 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.
26 + 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).
27
28 **A hashing example with multi-modality inputs**
29 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: