diff --git a/bench_shared.sh b/bench_shared.sh
new file mode 100644
index 00000000..ae0dde4f
--- /dev/null
+++ b/bench_shared.sh
@@ -0,0 +1,90 @@
+#!/bin/bash
+set -euo pipefail
+cat << 'PYEOF' | CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-0}" python3 -u -
+import torch, importlib.util, time
+torch.cuda.set_device(0)
+dev = torch.device("cuda:0")
+
+SO = "qwen3_6_scripts/prebuilt/corex-3.2.3-ivcore10"
+def load_so(name):
+    spec = importlib.util.spec_from_file_location(name, f"{SO}/{name}.so")
+    m = importlib.util.module_from_spec(spec); spec.loader.exec_module(m); return m
+
+bridge = load_so("ix_moe_bridge")
+act_m = load_so("xllm_activation")
+
+H = 2048
+I_shared = 128
+
+x = torch.randn(1, H, device=dev, dtype=torch.float16)
+w_gu = torch.randn(2*I_shared, H, device=dev, dtype=torch.float16) * 0.01
+w_down = torch.randn(H, I_shared, device=dev, dtype=torch.float16) * 0.01
+
+def bench(name, fn, N=1000):
+    for _ in range(100): fn()
+    torch.cuda.synchronize()
+    t0 = time.perf_counter()
+    for _ in range(N): fn()
+    torch.cuda.synchronize()
+    us = (time.perf_counter() - t0) / N * 1e6
+    print(f"  {name:45s}: {us:8.1f} us")
+    return us
+
+print("=== ix_moe_bridge.linear probe ===")
+linear_ok = False
+for desc, args in [("(x,w)", (x, w_gu)),
+                    ("(x,w,None)", (x, w_gu, None)),
+                    ("(x,w,bias0)", (x, w_gu, torch.zeros(2*I_shared,device=dev,dtype=torch.float16)))]:
+    try:
+        out = bridge.linear(*args); torch.cuda.synchronize()
+        print(f"  linear{desc}: OK shape={out.shape}")
+        linear_ok = True; break
+    except Exception as e:
+        print(f"  linear{desc}: {str(e)[:80]}")
+
+print("\n=== Shared expert benchmarks ===")
+act_buf = torch.empty(1, I_shared, device=dev, dtype=torch.float16)
+
+def shared_torch():
+    gu = torch.nn.functional.linear(x, w_gu)
+    g, u = gu.chunk(2, dim=-1)
+    act = torch.sigmoid(g) * g * u
+    return torch.nn.functional.linear(act, w_down)
+bench("A: torch linear + torch silu", shared_torch)
+
+def shared_xllm_silu():
+    gu = torch.nn.functional.linear(x, w_gu)
+    act_m.silu_and_mul(act_buf, gu)
+    return torch.nn.functional.linear(act_buf, w_down)
+bench("B: torch linear + xllm silu", shared_xllm_silu)
+
+if linear_ok:
+    try:
+        _ = bridge.linear(x, w_gu)
+        def shared_bridge():
+            gu = bridge.linear(x, w_gu)
+            act_m.silu_and_mul(act_buf, gu)
+            return bridge.linear(act_buf, w_down)
+        bench("C: bridge linear + xllm silu", shared_bridge)
+    except:
+        try:
+            b_gu = torch.zeros(2*I_shared,device=dev,dtype=torch.float16)
+            b_dn = torch.zeros(H,device=dev,dtype=torch.float16)
+            def shared_bridge_b():
+                gu = bridge.linear(x, w_gu, b_gu)
+                act_m.silu_and_mul(act_buf, gu)
+                return bridge.linear(act_buf, w_down, b_dn)
+            bench("C: bridge linear(bias0) + xllm silu", shared_bridge_b)
+        except Exception as e:
+            print(f"  C failed: {e}")
+
+print("\n=== Step breakdown ===")
+bench("gate_up F.linear (1,2048)@(256,2048)^T", lambda: torch.nn.functional.linear(x, w_gu))
+gu_t = torch.nn.functional.linear(x, w_gu)
+bench("silu_and_mul", lambda: act_m.silu_and_mul(act_buf, gu_t))
+bench("down F.linear (1,128)@(2048,128)^T", lambda: torch.nn.functional.linear(act_buf, w_down))
+
+print("\n=== matmul vs F.linear ===")
+bench("torch.mm(x, w_gu.T)", lambda: torch.mm(x, w_gu.t()))
+bench("F.linear(x, w_gu)", lambda: torch.nn.functional.linear(x, w_gu))
+PYEOF
\ No newline at end of file