diff --git a/routellm/routers/matrix_factorization/model.py b/routellm/routers/matrix_factorization/model.py
index 09fbb25..f292b8d 100644
--- a/routellm/routers/matrix_factorization/model.py
+++ b/routellm/routers/matrix_factorization/model.py
@@ -1,7 +1,7 @@
 import torch
 from huggingface_hub import PyTorchModelHubMixin
 
-from routellm.routers.similarity_weighted.utils import OPENAI_CLIENT
+from routellm.routers.similarity_weighted.utils import get_openai_client
 
 MODEL_IDS = {
     "RWKV-4-Raven-14B": 0,
@@ -110,7 +110,8 @@ def forward(self, model_id, prompt):
         model_embed = torch.nn.functional.normalize(model_embed, p=2, dim=1)
 
         prompt_embed = (
-            OPENAI_CLIENT.embeddings.create(input=[prompt], model=self.embedding_model)
+            get_openai_client()
+            .embeddings.create(input=[prompt], model=self.embedding_model)
             .data[0]
             .embedding
         )
diff --git a/routellm/routers/routers.py b/routellm/routers/routers.py
index 0096c0a..37e07cc 100644
--- a/routellm/routers/routers.py
+++ b/routellm/routers/routers.py
@@ -16,9 +16,9 @@
 from routellm.routers.causal_llm.model import CausalLLMClassifier
 from routellm.routers.matrix_factorization.model import MODEL_IDS, MFModel
 from routellm.routers.similarity_weighted.utils import (
-    OPENAI_CLIENT,
     compute_elo_mle_with_tie,
     compute_tiers,
+    get_openai_client,
     preprocess_battles,
 )
 
@@ -180,7 +180,7 @@ def calculate_strong_win_rate(
     ):
         prompt_emb = (
             (
-                OPENAI_CLIENT.embeddings.create(
+                get_openai_client().embeddings.create(
                     input=[prompt], model=self.embedding_model
                 )
             )
diff --git a/routellm/routers/similarity_weighted/utils.py b/routellm/routers/similarity_weighted/utils.py
index 19035ce..435fd07 100644
--- a/routellm/routers/similarity_weighted/utils.py
+++ b/routellm/routers/similarity_weighted/utils.py
@@ -1,3 +1,4 @@
+import functools
 import json
 import math
 import os
@@ -8,7 +9,18 @@
 from sklearn.linear_model import LogisticRegression
 
 choices = ["A", "B", "C", "D"]
-OPENAI_CLIENT = OpenAI()
+
+
+@functools.lru_cache(maxsize=1)
+def get_openai_client():
+    """Lazily instantiate (and cache) the OpenAI client.
+
+    Constructing ``OpenAI()`` requires ``OPENAI_API_KEY`` to be set. Creating it
+    at import time would force every router to need an API key, even local ones
+    (e.g. ``bert``, ``causal_llm``) that never call OpenAI. Deferring creation to
+    first use keeps those routers importable without any credentials.
+    """
+    return OpenAI()
 
 
 def compute_tiers(model_ratings, num_tiers):