diff --git a/promql/engine.go b/promql/engine.go
index e2092a800..57a6e7b02 100644
--- a/promql/engine.go
+++ b/promql/engine.go
@@ -1143,7 +1143,11 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 		}
 	}
 	enh := &EvalNodeHelper{Out: make(Vector, 0, biggestLen)}
-	seriess := make(map[uint64]Series, biggestLen) // Output series by series hash.
+	type seriesAndTimestamp struct {
+		Series
+		ts int64
+	}
+	seriess := make(map[uint64]seriesAndTimestamp, biggestLen) // Output series by series hash.
 	tempNumSamples := ev.currentSamples
 
 	var (
@@ -1228,9 +1232,6 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 		// Make the function call.
 		enh.Ts = ts
 		result, ws := funcCall(args, bufHelpers, enh)
-		if result.ContainsSameLabelset() {
-			ev.errorf("vector cannot contain metrics with the same labelset")
-		}
 		enh.Out = result[:0] // Reuse result vector.
 		warnings = append(warnings, ws...)
 
@@ -1247,6 +1248,9 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 
 		// If this could be an instant query, shortcut so as not to change sort order.
 		if ev.endTimestamp == ev.startTimestamp {
+			if result.ContainsSameLabelset() {
+				ev.errorf("vector cannot contain metrics with the same labelset")
+			}
 			mat := make(Matrix, len(result))
 			for i, s := range result {
 				if s.H == nil {
@@ -1264,8 +1268,13 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 		for _, sample := range result {
 			h := sample.Metric.Hash()
 			ss, ok := seriess[h]
-			if !ok {
-				ss = Series{Metric: sample.Metric}
+			if ok {
+				if ss.ts == ts { // If we've seen this output series before at this timestamp, it's a duplicate.
+					ev.errorf("vector cannot contain metrics with the same labelset")
+				}
+				ss.ts = ts
+			} else {
+				ss = seriesAndTimestamp{Series{Metric: sample.Metric}, ts}
 			}
 			if sample.H == nil {
 				if ss.Floats == nil {
@@ -1292,7 +1301,7 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 	// Assemble the output matrix. By the time we get here we know we don't have too many samples.
 	mat := make(Matrix, 0, len(seriess))
 	for _, ss := range seriess {
-		mat = append(mat, ss)
+		mat = append(mat, ss.Series)
 	}
 	ev.currentSamples = originalNumSamples + mat.TotalSamples()
 	ev.samplesStats.UpdatePeak(ev.currentSamples)