diff --git a/tests/fmha_v3_stage_c_example9.py b/tests/fmha_v3_stage_c_example9.py
index 94303c6b..baa0afd4 100644
--- a/tests/fmha_v3_stage_c_example9.py
+++ b/tests/fmha_v3_stage_c_example9.py
@@ -132,10 +132,11 @@ class FmhaV3StageCMulti:
         tma_v,mV = cute.nvgpu.make_tiled_tma_atom_B(utils.sm100.cluster_shape_to_tma_atom_B(self.cluster_shape_mn,pv_mma.thr_id),v_fmha,v_s,self.pv_mma_tiler,pv_mma,self.cluster_layout_vmnk.shape)
         epi_s = cute.select(self.c_smem_s,mode=[0,1])
         tma_c,mC = cpasync.make_tiled_tma_atom(cpasync.CopyBulkTensorTileS2GOp(),c,epi_s,self.epi_tile)
-        self._kernel(qk_mma,pv_mma,tma_q,mQ,tma_k,mK,tma_v,mV,tma_c,mC,self.cluster_layout_vmnk,self.q_smem_s,self.k_smem_s,self.v_smem_s,self.p_tmem_s,self.c_smem_s,self.epi_tile).launch(grid=(1,1,1),block=[self.threads_per_cta,1,1],stream=stream)
+        seqlen_k = Int32(self.s_k)
+        self._kernel(qk_mma,pv_mma,tma_q,mQ,tma_k,mK,tma_v,mV,tma_c,mC,self.cluster_layout_vmnk,self.q_smem_s,self.k_smem_s,self.v_smem_s,self.p_tmem_s,self.c_smem_s,self.epi_tile,seqlen_k).launch(grid=(1,1,1),block=[self.threads_per_cta,1,1],stream=stream)
 
     @cute.kernel
-    def _kernel(self, qk_mma, pv_mma, tma_q, mQ, tma_k, mK, tma_v, mV, tma_c, mC, cl_vmnk, q_smem_s, k_smem_s, v_smem_s, p_tmem_s, c_smem_s, epi_tile):
+    def _kernel(self, qk_mma, pv_mma, tma_q, mQ, tma_k, mK, tma_v, mV, tma_c, mC, cl_vmnk, q_smem_s, k_smem_s, v_smem_s, p_tmem_s, c_smem_s, epi_tile, seqlen_k):
         warp_idx = cute.arch.make_warp_uniform(cute.arch.warp_idx())
         tidx,_,_ = cute.arch.thread_idx()
         if warp_idx == self.tma_warp_id:
@@ -217,10 +218,17 @@ class FmhaV3StageCMulti:
             cute.copy(tma_q, tAgQ[(None, Int32(0))], tAsQ[(None, qh.index)], tma_bar_ptr=qh.barrier)
             qp.tail()
             kvp.reset()
+            # Dynamic start coordinate: derive from runtime seqlen_k.
+            # The JIT can't constant-fold seqlen_k - seqlen_k since seqlen_k
+            # is a kernel argument. This forces kv_coord to be a tracked
+            # SSA value that propagates through the loop iterations.
+            seqlen_k_tiles = seqlen_k // Int32(128)
+            kv_coord = seqlen_k_tiles - seqlen_k_tiles  # dynamic zero
             for kt in cutlass.range(0, n_kv_tiles, 1, unroll=1):
                 kvh = kvp.acquire_and_advance()
-                cute.copy(tma_k, tBgK[(None, kt)], tBsK[(None, kvh.index)], tma_bar_ptr=kvh.barrier)
-                cute.copy(tma_v, tVgV[(None, kt)], tVsV[(None, kvh.index)], tma_bar_ptr=kvh.barrier)
+                cute.copy(tma_k, tBgK[(None, kv_coord)], tBsK[(None, kvh.index)], tma_bar_ptr=kvh.barrier)
+                cute.copy(tma_v, tVgV[(None, kv_coord)], tVsV[(None, kvh.index)], tma_bar_ptr=kvh.barrier)
+                kv_coord += 1
             kvp.tail()
 
         # ===== MMA warp =====