diff --git a/litgpt/api.py b/litgpt/api.py
index 6eb0281fea..2ad0bc926f 100644
--- a/litgpt/api.py
+++ b/litgpt/api.py
@@ -239,6 +239,9 @@ def distribute(
                 "Support for multiple devices is currently only implemented for generate_strategy='sequential'|'tensor_parallel'."
             )
 
+        if precision is None:
+            precision = get_default_supported_precision(training=False)
+
         plugins = None
         if quantize is not None and quantize.startswith("bnb."):
             if "mixed" in precision:
diff --git a/litgpt/deploy/serve.py b/litgpt/deploy/serve.py
index c86d2abbc5..262aee4252 100644
--- a/litgpt/deploy/serve.py
+++ b/litgpt/deploy/serve.py
@@ -53,6 +53,10 @@ def setup(self, device: str) -> None:
         print("Initializing model...")
         self.llm = LLM.load(
             model=self.checkpoint_dir,
+            distribute=None
+        )
+
+        self.llm.distribute(
             accelerator=accelerator,
             quantize=self.quantize,
             precision=self.precision
diff --git a/tests/test_serve.py b/tests/test_serve.py
index 23eefdb8c7..8c29f90486 100644
--- a/tests/test_serve.py
+++ b/tests/test_serve.py
@@ -6,6 +6,7 @@
 import torch
 import requests
 import subprocess
+from tests.conftest import RunIf
 import threading
 import time
 import yaml
@@ -54,3 +55,46 @@ def run_server():
         if process:
             process.kill()
         server_thread.join()
+
+
+@RunIf(min_cuda_gpus=1)
+def test_quantize(tmp_path):
+    seed_everything(123)
+    ours_config = Config.from_name("pythia-14m")
+    download_from_hub(repo_id="EleutherAI/pythia-14m", tokenizer_only=True, checkpoint_dir=tmp_path)
+    shutil.move(str(tmp_path / "EleutherAI" / "pythia-14m" / "tokenizer.json"), str(tmp_path))
+    shutil.move(str(tmp_path / "EleutherAI" / "pythia-14m" / "tokenizer_config.json"), str(tmp_path))
+    ours_model = GPT(ours_config)
+    checkpoint_path = tmp_path / "lit_model.pth"
+    torch.save(ours_model.state_dict(), checkpoint_path)
+    config_path = tmp_path / "model_config.yaml"
+    with open(config_path, "w", encoding="utf-8") as fp:
+        yaml.dump(asdict(ours_config), fp)
+
+    run_command = [
+        "litgpt", "serve", tmp_path, "--quantize", "bnb.nf4"
+    ]
+
+    process = None
+
+    def run_server():
+        nonlocal process
+        try:
+            process = subprocess.Popen(run_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
+            stdout, stderr = process.communicate(timeout=10)
+        except subprocess.TimeoutExpired:
+            print('Server start-up timeout expired')
+
+    server_thread = threading.Thread(target=run_server)
+    server_thread.start()
+
+    time.sleep(10)
+
+    try:
+        response = requests.get("http://127.0.0.1:8000")
+        print(response.status_code)
+        assert response.status_code == 200, "Server did not respond as expected."
+    finally:
+        if process:
+            process.kill()
+        server_thread.join()