diff --git a/test/wenet/text/test_parallel.py b/test/wenet/text/test_parallel.py
new file mode 100644
index 000000000..28a0f37b2
--- /dev/null
+++ b/test/wenet/text/test_parallel.py
@@ -0,0 +1,42 @@
+from functools import partial
+from multiprocessing import Pool
+from wenet.text.base_tokenizer import BaseTokenizer
+
+from wenet.text.bpe_tokenizer import BpeTokenizer
+from wenet.text.whisper_tokenizer import WhisperTokenizer
+
+
+def consistency(tokenizer: BaseTokenizer, line: str) -> str:
+    return tokenizer.detokenize(tokenizer.tokenize(line)[1])[0]
+
+
+def test_whisper_tokenzier_parallel():
+
+    inputs = ["it's ok", "wenet is simple", "test for new io"]
+    tokenizer = WhisperTokenizer(False)
+
+    partial_tokenize = partial(consistency, tokenizer)
+    with Pool(processes=len(inputs)) as pool:
+        results = pool.map(partial_tokenize, inputs)
+
+    inputs.sort()
+    results.sort()
+
+    assert all(h == r for (h, r) in zip(results, inputs))
+
+
+def test_bpe_tokenzier_parallel():
+
+    symbol_table_path = "test/resources/librispeech.words.txt"
+    bpe_model = "test/resources/librispeech.train_960_unigram5000.bpemodel"
+
+    inputs = ["WENR IS SIMPLE", "GOOD"]
+    tokenizer = BpeTokenizer(bpe_model, symbol_table_path)
+    partial_tokenize = partial(consistency, tokenizer)
+    with Pool(processes=len(inputs)) as pool:
+        results = pool.map(partial_tokenize, inputs)
+
+    inputs.sort()
+    results.sort()
+
+    assert all(h == r for (h, r) in zip(results, inputs))