diff --git a/tools/bench/runner.py b/tools/bench/runner.py
index 3118f28..7056f16 100644
--- a/tools/bench/runner.py
+++ b/tools/bench/runner.py
@@ -134,7 +134,7 @@ def build_endpoints(args) -> list[SystemEndpoint]:
                 model_id=args.llama_model_id,
                 launch_cmd=llama_cpp_launch_cmd(
                     args.llama_bin, gguf, args.llama_port,
-                    n_parallel=args.max_batch, ctx_size=args.max_seq_len,
+                    n_parallel=args.max_batch, ctx_per_slot=args.max_seq_len,
                 ),
                 # llama-server's health endpoint also returns 200 only when model is loaded.
                 health_path="/health",
diff --git a/tools/bench/servers.py b/tools/bench/servers.py
index 6961feb..993f2ba 100644
--- a/tools/bench/servers.py
+++ b/tools/bench/servers.py
@@ -129,17 +129,22 @@ def llama_cpp_launch_cmd(
     port: int,
     *,
     n_parallel: int,
-    ctx_size: int,
+    ctx_per_slot: int,
     n_gpu_layers: int = 99,
 ) -> list[str]:
+    # llama.cpp DIVIDES total -c across --parallel slots: per-slot context is
+    # n_ctx / n_parallel. xserv gives each sequence the full max_seq_len, so to
+    # match we must set total -c = ctx_per_slot * n_parallel. Getting this wrong
+    # silently truncates long generations (e.g. AIME) on llama.cpp's side.
+    total_ctx = ctx_per_slot * n_parallel
     return [
         bin_path,
         "-m", gguf_path,
         "--port", str(port),
         "--host", "0.0.0.0",
-        "-c", str(ctx_size),
+        "-c", str(total_ctx),
         "-ngl", str(n_gpu_layers),
         "--parallel", str(n_parallel),
-        # Be quiet by default; the log file already captures stderr.
-        "--log-disable",
+        # NOTE: do NOT pass --log-disable; its startup log reports per-slot
+        # n_ctx, which is exactly the diagnostic that catches ctx misconfig.
     ]