diff --git a/docs/user_guide/appendix/performance_tips.ipynb b/docs/user_guide/appendix/performance_tips.ipynb
index 199b1c30..7a3ddc98 100644
--- a/docs/user_guide/appendix/performance_tips.ipynb
+++ b/docs/user_guide/appendix/performance_tips.ipynb
@@ -278,6 +278,18 @@
     "number of workers times the FFT threads at or below your physical core count. FFTW also exposes its planner through\n",
     "`fftw.planning_effort`; more patient planning can pay off for long-running simulations that reuse one grid size.\n",
     "\n",
+    "The same principle applies to Numba, which a few CPU-only code paths use directly — the\n",
+    "real-space multislice algorithm among them. Numba's thread pool follows `OMP_NUM_THREADS` if it\n",
+    "is set, or every visible core otherwise, and `NUMBA_NUM_THREADS` overrides that independently of\n",
+    "the other libraries above. These kernels are memory-bandwidth-bound and scale poorly past a\n",
+    "handful of threads even in isolation, so a large value rarely helps a single computation —\n",
+    "benchmark before assuming your full core count is best. Once Dask is already running many chunks\n",
+    "concurrently, keeping this low costs nothing at worst, and can measurably help: when the number\n",
+    "of concurrent workers already exceeds your physical core count — common once a worker pool is\n",
+    "sized to logical rather than physical cores — each kernel call claiming its own extra threads adds\n",
+    "contention with nothing left to actually parallelize into, and can cost real throughput rather\n",
+    "than merely fail to gain any.\n",
+    "\n",
     "### Use \"good\" numbers of `gpts`\n",
     "\n",
     "FFT implementations are most efficient for array sizes that factor into small primes (2, 3, 5 and 7). Since the exact\n",