diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt
index 2217a4340135..38216035f855 100644
--- a/tests/integration/test_lists/waives.txt
+++ b/tests/integration/test_lists/waives.txt
@@ -284,9 +284,6 @@ test_e2e.py::test_ptp_quickstart_advanced_deepseek_r1_w4afp8_8gpus[DeepSeek-R1-W
 test_e2e.py::test_ptp_quickstart_bert[TRTLLM-BertForSequenceClassification-bert/bert-base-uncased-yelp-polarity] SKIP (https://nvbugs/6605819)
 test_e2e.py::test_ptp_quickstart_bert[VANILLA-BertForSequenceClassification-bert/bert-base-uncased-yelp-polarity] SKIP (bug pending, tracked in PR 17414)
 unittest/_torch/attention/sparse/dsa/test_req_idx_per_token.py::test_on_update_kv_lens_rebuilds_stale_map SKIP (https://nvbugs/6574939)
-unittest/_torch/attention/sparse/msa/test_minimax_m3_index_decode_score.py::test_index_decode_score_matches_msa_proxy[dtype0] SKIP (https://nvbugs/6669902)
-unittest/_torch/attention/sparse/msa/test_minimax_m3_index_decode_score.py::test_index_decode_score_matches_msa_proxy[dtype1] SKIP (https://nvbugs/6669902)
-unittest/_torch/attention/sparse/msa/test_minimax_m3_sparse_attn_decode.py::test_sparse_decode_matches_msa_kernel SKIP (https://nvbugs/6669902)
 unittest/_torch/attention/sparse/msa/test_msa_backend.py::test_msa_paged_hnd_input_materializes_unaligned_outer_stride SKIP (https://nvbugs/6661846)
 unittest/_torch/attention/test_attention_backends.py::test_attention_backend[exaone_moe_gqa_swa128-ctx-bf16-HND-p32-v1] SKIP (https://nvbugs/6668773)
 unittest/_torch/attention/test_attention_backends.py::test_attention_backend[qwen2_0_5b_gqa_hd64-ctx-bf16-HND-p32-v1] SKIP (https://nvbugs/6641268)
diff --git a/tests/microbenchmarks/minimax_m3_index_decode_score.py b/tests/microbenchmarks/minimax_m3_index_decode_score.py
index eb1d344a552a..f58d288cedbf 100644
--- a/tests/microbenchmarks/minimax_m3_index_decode_score.py
+++ b/tests/microbenchmarks/minimax_m3_index_decode_score.py
@@ -28,15 +28,7 @@
 
 def _flat_page_table(block_table: torch.Tensor, kv_lens_cpu: torch.Tensor) -> torch.Tensor:
     """Flatten a block table into the per-request page ids fmha_sm100 consumes."""
-    batch, max_pages = block_table.shape
-    intra = torch.arange(PAGE_SIZE, dtype=torch.int32)
-    req_to_token = (block_table.cpu().to(torch.int32) * PAGE_SIZE).unsqueeze(2) + intra
-    return build_kv_page_indices(
-        req_to_token.reshape(batch, max_pages * PAGE_SIZE),
-        torch.arange(batch, dtype=torch.int32),
-        kv_lens_cpu,
-        PAGE_SIZE,
-    )
+    return build_kv_page_indices(block_table.cpu().to(torch.int32), kv_lens_cpu, PAGE_SIZE)
 
 
 def _time_us(fn, warmup: int = 20, iters: int = 100) -> float: