diff --git a/backend/open_webui/env.py b/backend/open_webui/env.py
index b17df7340a..c3a7da82e2 100644
--- a/backend/open_webui/env.py
+++ b/backend/open_webui/env.py
@@ -7,7 +7,9 @@ import pkgutil
 import re
 import shutil
 import sys
+import threading
 import traceback
+from contextlib import nullcontext
 from pathlib import Path
 from typing import Any, Optional
 from uuid import uuid4
@@ -66,6 +68,9 @@ if sys.platform == 'darwin' and DEVICE_TYPE == 'cpu':
     except Exception:
         pass
 
+# Torch MPS inference is not thread-safe and a concurrent call kills the whole process.
+MPS_INFERENCE_LOCK = threading.Lock() if DEVICE_TYPE == 'mps' else nullcontext()
+
 ####################################
 # LOGGING
 ####################################
diff --git a/backend/open_webui/retrieval/utils.py b/backend/open_webui/retrieval/utils.py
index 294309984e..ec7c73770e 100644
--- a/backend/open_webui/retrieval/utils.py
+++ b/backend/open_webui/retrieval/utils.py
@@ -32,6 +32,7 @@ from open_webui.env import (
     BYPASS_RETRIEVAL_ACCESS_CONTROL,
     ENABLE_FORWARD_USER_INFO_HEADERS,
     ENABLE_RETRIEVAL_UNSCOPED_COLLECTIONS,
+    MPS_INFERENCE_LOCK,
     OFFLINE_MODE,
 )
 from open_webui.models.access_grants import AccessGrants
@@ -1116,17 +1117,16 @@ def get_embedding_function(
                     'SentenceTransformer model name, or configure an external '
                     'RAG_EMBEDDING_ENGINE (ollama, openai, azure_openai).'
                 )
-            return await asyncio.to_thread(
-                (
-                    lambda query, prefix=None: embedding_function.encode(
+
+            def encode():
+                with MPS_INFERENCE_LOCK:
+                    return embedding_function.encode(
                         query,
                         batch_size=int(embedding_batch_size),
                         **({'prompt': prefix} if prefix else {}),
                     ).tolist()
-                ),
-                query,
-                prefix,
-            )
+
+            return await asyncio.to_thread(encode)
 
         return async_embedding_function
     elif embedding_engine in ['ollama', 'openai', 'azure_openai']:
@@ -1250,9 +1250,14 @@ def get_reranking_function(reranking_engine, reranking_model, reranking_function
             [(query, doc.page_content) for doc in documents], user=user
         )
     else:
-        return lambda query, documents, user=None: reranking_function.predict(
-            [(query, doc.page_content) for doc in documents], batch_size=int(reranking_batch_size)
-        )
+
+        def predict(query, documents, user=None):
+            with MPS_INFERENCE_LOCK:
+                return reranking_function.predict(
+                    [(query, doc.page_content) for doc in documents], batch_size=int(reranking_batch_size)
+                )
+
+        return predict
 
 
 # UUIDs, SHA-256 digests, and prefixed variants thereof all fit [A-Za-z0-9_-].
diff --git a/backend/open_webui/routers/evaluations.py b/backend/open_webui/routers/evaluations.py
index 8a6bf71f4a..e1c7543eea 100644
--- a/backend/open_webui/routers/evaluations.py
+++ b/backend/open_webui/routers/evaluations.py
@@ -4,6 +4,7 @@ from typing import Optional
 from fastapi import APIRouter, Depends, HTTPException, Request, status
 from fastapi.concurrency import run_in_threadpool
 from open_webui.constants import ERROR_MESSAGES
+from open_webui.env import MPS_INFERENCE_LOCK
 from open_webui.events import EVENTS, publish_event
 from open_webui.internal.db import get_async_session
 from open_webui.models.config import Config
@@ -179,8 +180,9 @@ def _compute_similarities(feedbacks: list[LeaderboardFeedbackData], query: str)
         return {}
 
     try:
-        tag_embeddings = embedding_model.encode(all_tags)
-        query_embedding = embedding_model.encode([query])[0]
+        with MPS_INFERENCE_LOCK:
+            tag_embeddings = embedding_model.encode(all_tags)
+            query_embedding = embedding_model.encode([query])[0]
     except Exception as e:
         log.error(f'Embedding error: {e}')
         return {}