diff --git a/vllm_gaudi/extension/bucketing/common.py b/vllm_gaudi/extension/bucketing/common.py
index 7992cf8a..13565fa9 100644
--- a/vllm_gaudi/extension/bucketing/common.py
+++ b/vllm_gaudi/extension/bucketing/common.py
@@ -245,6 +245,8 @@ def expand_to_neighbor_buckets(bs_idx, bs_range, query_idx, query_range, max_num
                       (bs_idx + 1, query_idx + 1)]
         valid = bs_range[bs_idx] * query_range[query_idx] <= max_num_batched_tokens
         if not valid:
+            omitted_buckets.add(("bs_range[bs_idx] * query_range[query_idx] <= max_num_batched_tokens",
+                                 "-> bs, quesry: ", bs_idx, query_idx))
             return {}
         valid_candidates = [(b_idx, q_idx) for b_idx, q_idx in candidates
                             if b_idx < len(bs_range) and q_idx < len(query_range)]
@@ -253,17 +255,30 @@ def expand_to_neighbor_buckets(bs_idx, bs_range, query_idx, query_range, max_num
     # filter rules for buckets
     # prompt
     def not_over_max_model_len(bs, query, ctx):
+        if not query + ctx * block_size <= max_model_len:
+            omitted_buckets.add(
+                ("condition: query + ctx * block_size <= max_model_len", "-> bs, quesry, ctx: ", bs, query, ctx))
         return query + ctx * block_size <= max_model_len
 
     def ctx_not_over_max_ctx_for_merged_prefill(bs, query, ctx):
+        if not ctx <= max_num_prefill_seqs * math.ceil(
+            (max_model_len - math.floor(query / max_num_prefill_seqs)) // block_size):
+            omitted_buckets.add((
+                "ctx <= max_num_prefill_seqs * math.ceil((max_model_len - math.floor(query / max_num_prefill_seqs)) // block_size)",
+                "-> bs, quesry, ctx: ", bs, query, ctx))
         return ctx <= max_num_prefill_seqs * math.ceil(
             (max_model_len - math.floor(query / max_num_prefill_seqs)) // block_size)
 
     # decode
     def block_not_greater_than_max_model_len(bs, query, ctx):
+        if not ctx <= bs * math.ceil(max_model_len / block_size):
+            omitted_buckets.add(("condition: ctx <= bs * math.ceil(max_model_len / block_size)", "-> bs, quesry, ctx: ",
+                                 bs, query, ctx))
         return ctx <= bs * math.ceil(max_model_len / block_size)
 
     def batch_size_smaller_than_blocks(bs, query, ctx):
+        if not bs <= ctx:
+            omitted_buckets.add(("condition: bs <= ctx, ", "-> bs, query, ctx: ", bs, query, ctx))
         return bs <= ctx
 
     filters_map = {
@@ -289,6 +304,7 @@ def get_filters(is_prompt, use_merged_prefill, use_contiguous_pa):
 
     buckets = set()
     buckets_2d = set()
+    omitted_buckets = set()
     filters = get_filters(is_prompt, use_merged_prefill, use_contiguous_pa)
     for bs_idx, bs in enumerate(bs_range):
         for query_idx, query in enumerate(query_range):
@@ -299,6 +315,15 @@ def get_filters(is_prompt, use_merged_prefill, use_contiguous_pa):
         for ctx in ctx_range:
             if all(bucket_filter(bs, query, ctx) for bucket_filter in filters):
                 buckets.add((bs, query, ctx))
+    if not buckets:
+        phase = 'prompt' if is_prompt else 'decode'
+        for bucket in omitted_buckets:
+            logger().error(bucket)
+        raise RuntimeError(
+            "Generated 0 " + phase +
+            " buckets. Please use default exponential bucketing, VLLM_EXPONENTIAL_BUCKETING=true or generate linear warmup flags according to README"
+        )
+
     return sorted(buckets)