docs: VLLM_ENABLE_STARTUP_PLAN as an opt-in next to the compile cache

docs/configuration.md

@@ -90,6 +90,19 @@ cache: each vLLM version, model config and GPU type adds an entry.
 endpoint scaled to zero); vLLM rebuilds it. Set `VLLM_CACHE_ROOT=/root/.cache/vllm` to
 keep the cache in the container.
 
+Set `VLLM_ENABLE_STARTUP_PLAN=1` on the endpoint (`1` or `0` only; `true` fails the start)
+and vLLM also saves the KV-cache memory budget it measured under
+`$VLLM_CACHE_ROOT/startup_plan/`, keyed by the vLLM version, the model, cache, parallel and
+compilation config, the GPU name, total memory and compute capability, the torch/CUDA build
+and the rank. A later cold start with the same key and at least as much free GPU memory
+reuses the budget and skips the memory measurement and the CUDA-graph memory estimate;
+any mismatch, less free memory, or an explicit `KV_CACHE_MEMORY_BYTES` means it measures as
+before, with nothing to clean up. Plans follow `VLLM_CACHE_ROOT`, including the fallback
+above (an existing plan on the volume is not copied). Off by default: vLLM's key does not
+yet include `gpu_memory_utilization` (vllm-project/vllm#60143), so after changing
+`GPU_MEMORY_UTILIZATION` delete `$VLLM_CACHE_ROOT/startup_plan/` while no worker is
+starting, or unset the variable, or the old budget is reused.
+
 ## Speculative decoding
 
 Pass a full JSON config, which vLLM parses natively: