diff --git a/src/deepsparse/pipeline.py b/src/deepsparse/pipeline.py
index e2a1beeab1..aaa65409d8 100644
--- a/src/deepsparse/pipeline.py
+++ b/src/deepsparse/pipeline.py
@@ -27,6 +27,7 @@
     SchedulerGroup,
 )
 from deepsparse.subgraph_execute import SubGraphExecutor
+from deepsparse.tasks import SupportedTasks
 from deepsparse.utils import InferenceState, PipelineState
 from deepsparse.utils.subgraph import SubGraph
 from deepsparse.utils.time import TIMER_KEY, InferenceStages, TimerManager
@@ -139,7 +140,10 @@ def create(cls, task: str, **kwargs) -> "Pipeline":
                     "Pipeline was not created for the given task. The "
                     "provided task should be registered using the OperatorRegistry"
                 )
-        except Exception:
+        except Exception as e:
+            if SupportedTasks.is_text_generation(task):
+                raise e
+
             _LOGGER.warning(f"Could not create v2 '{task}' pipeline, trying legacy")
             from deepsparse.legacy import Pipeline
 
diff --git a/src/deepsparse/transformers/pipelines/text_generation/autoregressive_preprocess_operator.py b/src/deepsparse/transformers/pipelines/text_generation/autoregressive_preprocess_operator.py
index df4e587df3..01d2a664b5 100644
--- a/src/deepsparse/transformers/pipelines/text_generation/autoregressive_preprocess_operator.py
+++ b/src/deepsparse/transformers/pipelines/text_generation/autoregressive_preprocess_operator.py
@@ -51,7 +51,10 @@ def can_operate(self, inp: Any) -> bool:
         if inp.get("in_generation"):
             return True
 
-        if kv_cache.total_num_processed_tokens >= kv_cache.capacity:
+        if (
+            kv_cache.total_num_processed_tokens >= kv_cache.capacity
+            and inp.get("in_generation") is None
+        ):
             raise RuntimeError(
                 "Not enough kv_cache capacity to run generation. Please use a larger "
                 "sequence_length or a shorter prompt"