diff --git a/server/text_generation_server/models/flash_causal_lm.py b/server/text_generation_server/models/flash_causal_lm.py
index 8ab1a811..25c49183 100644
--- a/server/text_generation_server/models/flash_causal_lm.py
+++ b/server/text_generation_server/models/flash_causal_lm.py
@@ -887,11 +887,12 @@ class FlashCausalLMBatch(Batch):
             fsm_grammar_states=fsm_grammar_states,
         )
 
-        speculative_ids = (
-            torch.cat([b.speculative_ids for b in batches], dim=0)
-            if batches[0].speculative_ids is not None
-            else None
-        )
+        # We skip computing the speculative_ids when the batch size is too large, so
+        # we must check that all batches have them, otherwise they must be discarded
+        if get_speculate() > 0 and all(b.speculative_ids is not None for b in batches):
+            speculative_ids = torch.cat([b.speculative_ids for b in batches], dim=0)
+        else:
+            speculative_ids = None
 
         if adapter_segment_builder is not None:
             adapter_segments, adapter_segment_indices = adapter_segment_builder.build()
@@ -1718,7 +1719,13 @@ class FlashCausalLM(Model):
             new_position_ids = (
                 position_ids.unsqueeze(-1).expand(B, new_length) + arange
             ).view(-1)
-            slots = (slots.unsqueeze(-1).expand(B, new_length) + arange_int).view(-1)
+
+            # Slots can be discontiguous when prefix caching is enabled, so we need to expand the slot_indices,
+            # then update the slots with the additional indices to ensure we're grabbing the ones that have been
+            # allocated
+            slot_indices = (batch.slot_indices.unsqueeze(-1).expand(B, new_length) + arange_int).view(-1)
+            slots = batch.slots[slot_indices]
+            
             input_lengths = (
                 input_lengths.unsqueeze(-1).expand(B, new_length) + arange_int
             ).view(-1)