diff --git a/backends/exllamav3/model.py b/backends/exllamav3/model.py
index 330c4e1..1026faf 100644
--- a/backends/exllamav3/model.py
+++ b/backends/exllamav3/model.py
@@ -20,7 +20,7 @@ from exllamav3 import (
     Model,
     Tokenizer,
 )
-from exllamav3.cache import CacheLayer_fp16, CacheLayer_quant
+from exllamav3.cache import CacheLayer_quant
 from loguru import logger
 
 from backends.base_model_container import BaseModelContainer
@@ -76,6 +76,7 @@ class ExllamaV3Container(BaseModelContainer):
     max_seq_len: int = 4096
     cache_size: int = 4096
     cache_mode: str = "FP16"
+    draft_cache_mode: str = "FP16"
     chunk_size: int = 2048
     max_batch_size: Optional[int] = None
 
@@ -245,13 +246,35 @@ class ExllamaV3Container(BaseModelContainer):
                 v_bits=v_bits,
             )
         else:
-            self.cache = Cache(
-                self.model, max_num_tokens=self.cache_size, layer_type=CacheLayer_fp16
-            )
+            self.cache = Cache(self.model, max_num_tokens=self.cache_size)
 
         # Draft cache
         if self.use_draft_model:
-            self.draft_cache = Cache(self.draft_model, max_num_tokens = self.cache_size)
+            # Set draft cache mode
+            self.draft_cache_mode = unwrap(draft_args.get("draft_cache_mode"), "FP16")
+
+            # Alias Exl2 q-cache settings
+            match self.draft_cache_mode:
+                case "Q4":
+                    self.draft_cache_mode = "4,4"
+                case "Q6":
+                    self.draft_cache_mode = "6,6"
+                case "Q8":
+                    self.draft_cache_mode = "8,8"
+
+            split_draft_cache_mode = re.search(r"^([2-8])\s*,\s*([2-8])$", self.draft_cache_mode)
+            if split_draft_cache_mode:
+                draft_k_bits = int(split_draft_cache_mode.group(1))
+                draft_v_bits = int(split_draft_cache_mode.group(2))
+                self.draft_cache = Cache(
+                    self.draft_model,
+                    max_num_tokens=self.cache_size,
+                    layer_type=CacheLayer_quant,
+                    k_bits=draft_k_bits,
+                    v_bits=draft_v_bits,
+                )
+            else:
+                self.draft_cache = Cache(self.draft_model, max_num_tokens = self.cache_size)
 
         # Max batch size
         self.max_batch_size = unwrap(kwargs.get("max_batch_size"), 256)