diff --git a/backends/candle/src/lib.rs b/backends/candle/src/lib.rs
index 882cdb8a..ca3bff5f 100644
--- a/backends/candle/src/lib.rs
+++ b/backends/candle/src/lib.rs
@@ -500,7 +500,10 @@ impl Backend for CandleBackend {
         // Used for indexing in the raw_embeddings tensor
         let input_lengths: Vec<usize> = (0..batch.len())
             .map(|i| {
-                (batch.cumulative_seq_lengths[i + 1] - batch.cumulative_seq_lengths[i]) as usize
+                batch.cumulative_seq_lengths[i + 1]
+                    .checked_sub(batch.cumulative_seq_lengths[i])
+                    .expect("Invalid cumulative sequence lengths: sequence lengths must be non-decreasing")
+                    as usize
             })
             .collect();
 
@@ -565,3 +568,45 @@ impl<O> WrapErr<O> for Result<O, candle::Error> {
         self.map_err(|e| BackendError::Inference(e.to_string()))
     }
 }
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use text_embeddings_backend_core::Batch;
+
+    #[test]
+    #[should_panic(expected = "Invalid cumulative sequence lengths")]
+    fn test_invalid_cumulative_seq_lengths() {
+        // Create a mock backend for testing
+        let device = Device::Cpu;
+        let model = Box::new(MockModel);
+        let backend = CandleBackend { device, model };
+
+        // Create a batch with invalid cumulative sequence lengths (decreasing)
+        let batch = Batch {
+            input_ids: vec![1, 2, 3, 4],
+            token_type_ids: vec![0, 0, 0, 0],
+            position_ids: vec![0, 1, 2, 3],
+            cumulative_seq_lengths: vec![0, 3, 2], // Invalid: 3 > 2
+            max_length: 4,
+            pooled_indices: vec![0],
+            raw_indices: vec![],
+        };
+
+        // This should panic due to invalid cumulative sequence lengths
+        let _ = backend.embed(batch);
+    }
+
+    // Mock model for testing
+    struct MockModel;
+
+    impl crate::models::Model for MockModel {
+        fn is_padded(&self) -> bool {
+            false
+        }
+
+        fn embed(&self, _batch: Batch) -> candle::Result<(Option<candle::Tensor>, Option<candle::Tensor>)> {
+            Ok((None, None))
+        }
+    }
+}