diff --git a/src/fairseq2/generation/text.py b/src/fairseq2/generation/text.py
index e1dfa43c0..d2f90a437 100644
--- a/src/fairseq2/generation/text.py
+++ b/src/fairseq2/generation/text.py
@@ -153,6 +153,7 @@ class TextTranslator:
     _converter: SequenceToTextConverter
     _pad_idx: int
     _source_text_encoder: TextTokenEncoder
+    _max_source_len: Optional[int]
 
     def __init__(
         self,
@@ -160,6 +161,7 @@ def __init__(
         tokenizer: TextTokenizer,
         source_lang: Optional[str] = None,
         target_lang: Optional[str] = None,
+        max_source_len: Optional[int] = None,
     ) -> None:
         """
         :param generator:
@@ -170,6 +172,8 @@ def __init__(
             The source language.
         :param target_lang:
             The target language.
+        :param max_source_len:
+            The number of tokens above which the source sequence gets truncated (None or 0 for no truncation)
         """
         self._converter = SequenceToTextConverter(
             generator, tokenizer, "translation", target_lang
@@ -188,6 +192,7 @@ def __init__(
         self._source_text_encoder = tokenizer.create_encoder(
             task="translation", lang=source_lang, mode="source", device=device
         )
+        self._max_source_len = max_source_len
 
     def __call__(self, source_text: str) -> Tuple[str, Seq2SeqGeneratorOutput]:
         """
@@ -200,6 +205,9 @@ def __call__(self, source_text: str) -> Tuple[str, Seq2SeqGeneratorOutput]:
         """
         source_seq = self._source_text_encoder(source_text)
 
+        if self._max_source_len and source_seq.shape[0] > self._max_source_len:
+            source_seq = source_seq[: self._max_source_len]
+
         return self._converter(source_seq)
 
     def batch_translate(
@@ -220,6 +228,9 @@ def batch_translate(
 
         source_seq_list = [self._source_text_encoder(t) for t in source_texts]
 
+        if self._max_source_len:
+            source_seq_list = [seq[: self._max_source_len] for seq in source_seq_list]
+
         source_seqs, source_padding_mask = pad_seqs(source_seq_list, self._pad_idx)
 
         return self._converter.batch_convert(source_seqs, source_padding_mask)
diff --git a/tests/integration/models/test_nllb.py b/tests/integration/models/test_nllb.py
index ded0d680e..acddddce8 100644
--- a/tests/integration/models/test_nllb.py
+++ b/tests/integration/models/test_nllb.py
@@ -6,6 +6,7 @@
 
 from typing import Final
 
+import pytest
 import torch
 
 from fairseq2.generation import BeamSearchSeq2SeqGenerator, TextTranslator
@@ -25,7 +26,7 @@ def test_load_dense_distill_600m() -> None:
 
     tokenizer = load_nllb_tokenizer(model_name, progress=False)
 
-    generator = BeamSearchSeq2SeqGenerator(model, echo_prompt=True)
+    generator = BeamSearchSeq2SeqGenerator(model, echo_prompt=True, max_seq_len=128)
 
     translator = TextTranslator(
         generator, tokenizer, source_lang="eng_Latn", target_lang="deu_Latn"
@@ -34,3 +35,18 @@ def test_load_dense_distill_600m() -> None:
     text, _ = translator(ENG_SENTENCE)
 
     assert text == DEU_SENTENCE
+
+    # testing that truncation prevents length-related errors
+    with pytest.raises(
+        ValueError, match="The input sequence length must be less than or equal"
+    ):
+        text, _ = translator(ENG_SENTENCE * 20)
+
+    translator = TextTranslator(
+        generator,
+        tokenizer,
+        source_lang="eng_Latn",
+        target_lang="deu_Latn",
+        max_source_len=1024,
+    )
+    text, _ = translator(ENG_SENTENCE * 20)