diff --git a/src/compiler/execution.jl b/src/compiler/execution.jl
index cc8d3310..c3a74299 100644
--- a/src/compiler/execution.jl
+++ b/src/compiler/execution.jl
@@ -209,7 +209,37 @@ struct HostKernel{F,TT} <: AbstractKernel{F,TT}
     fun::ZeKernel
 end
 
+# Memoized: this sits on the per-launch path, not on a setup path.
+#
+# KernelAbstractions calls `launch_configuration` on every dispatch of a kernel
+# whose workgroupsize is `DynamicSize` and unspecified at the call site (see
+# src/oneAPIKernels.jl), so the `zeKernelGetProperties` round-trip below is paid
+# per launch. It dominates the launch: measured on a Data Center GPU Max 1550
+# with a no-op kernel, 96 us per launch with the query versus 9.7 us with the
+# workgroupsize pinned, all of it host-side. Launch-bound workloads pay this on
+# every kernel they dispatch.
+#
+# Safe to cache: the result is a function of the kernel and its device alone.
+# A ZeKernel's handle and module are fixed for its lifetime, and `maxGroupSize` /
+# `maxTotalGroupSize` are static properties of the compiled kernel -- neither the
+# ndrange nor any argument value reaches this computation.
+#
+# Keyed weakly on the ZeKernel rather than on its raw handle: a handle is only
+# unique among *live* kernels, so a handle key could let a destroyed kernel's
+# entry be inherited by a later kernel that reuses its address. The weak key ties
+# the entry to the kernel's own lifetime and needs no hook in oneL0's finalizer.
+const _launch_config_cache = WeakKeyDict{ZeKernel,Int}()
+
 function launch_configuration(kernel::HostKernel{F,TT}) where {F,TT}
+    fun = kernel.fun
+    cached = get(_launch_config_cache, fun, nothing)
+    cached === nothing || return cached
+    config = _launch_configuration_uncached(kernel)
+    _launch_config_cache[fun] = config
+    return config
+end
+
+function _launch_configuration_uncached(kernel::HostKernel{F,TT}) where {F,TT}
     # Level Zero's zeKernelSuggestGroupSize provides a launch configuration
     # that exactly cover the input size. This can result in very awkward
     # configurations, so roll our own version that behaves like CUDA's