diff --git a/qupulse/_program/tabor.py b/qupulse/_program/tabor.py
index b92c76f..690cfca 100644
--- a/qupulse/_program/tabor.py
+++ b/qupulse/_program/tabor.py
@@ -473,7 +473,11 @@ class TaborProgram(ProgramEntry):
         if np.any(segment_lengths % 16 > 0) or np.any(segment_lengths < 192):
             raise TaborException('At least one waveform has a length that is smaller 192 or not a multiple of 16')
 
+        # Deduplicate segments by their hash to avoid uploading identical waveforms multiple times
         segments = []
+        seen_hash_to_index = {}  # maps segment hash to index in segments list
+        unique_lengths_dict = {}  # maps segment hash to its length (first occurrence)
+        
         for i, waveform in enumerate(self._parsed_program.waveforms):
             t = time_array[:segment_lengths[i]]
             marker_time = t[::2]
@@ -484,11 +488,28 @@ class TaborProgram(ProgramEntry):
             marker_a = self._marker_data(waveform, marker_time, 0)
             marker_b = self._marker_data(waveform, marker_time, 1)
             segment = TaborSegment.from_sampled(ch_a=segment_a,
-                                   ch_b=segment_b,
-                                   marker_a=marker_a,
-                                   marker_b=marker_b)
-            segments.append(segment)
-        return segments, segment_lengths
+                                               ch_b=segment_b,
+                                               marker_a=marker_a,
+                                               marker_b=marker_b)
+            segment_hash = segment._hash
+            segment_len = segment_lengths[i]
+            
+            if segment_hash not in seen_hash_to_index:
+                seen_hash_to_index[segment_hash] = len(segments)
+                unique_lengths_dict[segment_hash] = segment_len
+                segments.append(segment)
+        
+        # Build unique lengths in order of first appearance among unique segments
+        unique_lengths = []
+        seen_in_order = set()
+        for segment in segments:
+            h = segment._hash
+            if h not in seen_in_order:
+                unique_lengths.append(unique_lengths_dict[h])
+                seen_in_order.add(h)
+        
+        return segments, np.array(unique_lengths, dtype=np.int64)
+
 
     def setup_single_sequence_mode(self) -> None:
         assert self.program.depth() == 1