diff --git a/examples/wechat_history_reader_leann.py b/examples/wechat_history_reader_leann.py
index 971ea74..d002174 100644
--- a/examples/wechat_history_reader_leann.py
+++ b/examples/wechat_history_reader_leann.py
@@ -78,7 +78,7 @@ def create_leann_index_from_multiple_wechat_exports(
         )
 
         # Create text splitter with 256 chunk size
-        text_splitter = SentenceSplitter(chunk_size=256, chunk_overlap=128)
+        text_splitter = SentenceSplitter(chunk_size=192, chunk_overlap=64)
 
         # Convert Documents to text strings and chunk them
         all_texts = []
diff --git a/packages/leann-core/src/leann/embedding_compute.py b/packages/leann-core/src/leann/embedding_compute.py
index ce85055..14a21f8 100644
--- a/packages/leann-core/src/leann/embedding_compute.py
+++ b/packages/leann-core/src/leann/embedding_compute.py
@@ -101,7 +101,7 @@ def compute_embeddings_sentence_transformers(
         if device == "mps":
             batch_size = 128  # MPS optimal batch size from benchmark
             if model_name == "Qwen/Qwen3-Embedding-0.6B":
-                batch_size = 64
+                batch_size = 32
         elif device == "cuda":
             batch_size = 256  # CUDA optimal batch size
         # Keep original batch_size for CPU