diff --git a/scripts/bench_moe.py b/scripts/bench_moe.py
index 644d22320..635ef6a79 100644
--- a/scripts/bench_moe.py
+++ b/scripts/bench_moe.py
@@ -86,6 +86,16 @@ def bench(fn, *args, iters=50, warmup=10, sync=True):
     return sum(times) / len(times)
 
 
+def estimate_moe_flops(tokens: int, hidden: int, inter: int, top_k: int) -> float:
+    """Estimate GEMM FLOPs for a SwiGLU MoE MLP.
+
+    Two up projections (w1,w3) + one down (w2), each token processed by top_k experts.
+    FLOPs ≈ 6 * (tokens * top_k) * hidden * inter (2*m*k*n per GEMM).
+    """
+    m_rep = tokens * top_k
+    return 6.0 * m_rep * hidden * inter
+
+
 def main():
     p = argparse.ArgumentParser(description="MoE microbenchmark")
     p.add_argument("--bsz", type=int, default=8)
@@ -139,9 +149,13 @@ def main():
         iters=args.iters,
         warmup=args.warmup,
     )
-    print(f"naive	{t_naive:.2f} ms	{tokens / (t_naive / 1000):.1f} tok/s")
+    flops_total = estimate_moe_flops(tokens, args.hidden, args.inter, args.top_k)
+    tflops_naive = flops_total / ((t_naive / 1000.0) * 1e12)
+    print(
+        f"naive\t{t_naive:.2f} ms\t{tokens / (t_naive / 1000):.1f} tok/s\t{tflops_naive:.2f} TFLOP/s"
+    )
 
-    # HF Triton (routing + stub compute for now)
+    # HF Triton (stub compute for now)
     os.environ.setdefault("AXOLOTL_MOE_BACKEND", "hf_triton")
     t_hf = forward_hf_triton
     y = t_hf(x, gate, experts, args.top_k)
@@ -149,12 +163,15 @@ def main():
         t_ms = bench(
             t_hf, x, gate, experts, args.top_k, iters=args.iters, warmup=args.warmup
         )
-        print(f"hf_triton	{t_ms:.2f} ms	{tokens / (t_ms / 1000):.1f} tok/s")
+        tflops = flops_total / ((t_ms / 1000.0) * 1e12)
+        print(
+            f"hf_triton\t{t_ms:.2f} ms\t{tokens / (t_ms / 1000):.1f} tok/s\t{tflops:.2f} TFLOP/s"
+        )
     else:
-        print("hf_triton	N/A (kernels hub not available)")
+        print("hf_triton\tN/A (kernels hub not available)")
 
     # torch_grouped placeholder — not yet implemented
-    print("torch_grouped	N/A (pending implementation)")
+    print("torch_grouped\tN/A (pending implementation)")
 
 
 if __name__ == "__main__":