diff --git a/vllm_mlx/scheduler.py b/vllm_mlx/scheduler.py
index eca61c43..74ec5a10 100644
--- a/vllm_mlx/scheduler.py
+++ b/vllm_mlx/scheduler.py
@@ -448,7 +448,16 @@ def _schedule_waiting(self) -> List[Request]:
                 break
 
             # Determine tokens to process and cache to use
-            tokens_to_process = request.remaining_tokens or request.prompt_token_ids
+            # Note: Don't use `remaining_tokens or prompt_token_ids` because empty list
+            # is falsy in Python. For exact cache match, remaining_tokens=[] but we should
+            # pass just the last token so BatchGenerator can start generation.
+            if request.remaining_tokens is not None and len(request.remaining_tokens) == 0:
+                # Exact cache match - pass only last token for generation kickoff
+                tokens_to_process = request.prompt_token_ids[-1:]
+            elif request.remaining_tokens:
+                tokens_to_process = request.remaining_tokens
+            else:
+                tokens_to_process = request.prompt_token_ids
             cache_to_use = request.prompt_cache  # May be None
 
             # Validate cache before using it
@@ -590,16 +599,18 @@ def _cleanup_finished(self, finished_ids: Set[str]) -> None:
             if request is not None and request.prompt_token_ids:
                 if self.block_aware_cache is not None:
                     # Store in paged cache
+                    # Key includes both prompt and output tokens for multi-turn chat caching
                     if hasattr(request, '_extracted_cache') and request._extracted_cache is not None:
                         try:
+                            full_token_sequence = list(request.prompt_token_ids) + list(request.output_token_ids)
                             self.block_aware_cache.store_cache(
                                 request_id,
-                                request.prompt_token_ids,
+                                full_token_sequence,
                                 request._extracted_cache,
                             )
                             logger.debug(
                                 f"Stored paged cache for request {request_id} "
-                                f"({len(request.prompt_token_ids)} tokens)"
+                                f"({len(full_token_sequence)} tokens: {len(request.prompt_token_ids)} prompt + {len(request.output_token_ids)} output)"
                             )
                         except Exception as e:
                             logger.debug(f"Failed to store paged cache for {request_id}: {e}")
@@ -609,15 +620,18 @@ def _cleanup_finished(self, finished_ids: Set[str]) -> None:
 
                 elif self.prefix_cache is not None:
                     # Store in standard prefix cache
+                    # Key includes both prompt and output tokens for multi-turn chat caching
+                    # The next turn's prompt will include the previous response
                     if hasattr(request, '_extracted_cache') and request._extracted_cache is not None:
                         try:
+                            full_token_sequence = list(request.prompt_token_ids) + list(request.output_token_ids)
                             self.prefix_cache.store_cache(
-                                request.prompt_token_ids,
+                                full_token_sequence,
                                 request._extracted_cache,
                             )
                             logger.debug(
                                 f"Stored cache for request {request_id} "
-                                f"({len(request.prompt_token_ids)} tokens)"
+                                f"({len(full_token_sequence)} tokens: {len(request.prompt_token_ids)} prompt + {len(request.output_token_ids)} output)"
                             )
                         except Exception as e:
                             logger.debug(f"Failed to store cache for {request_id}: {e}")