diff --git a/storage/remote/otlptranslator/prometheusremotewrite/metrics_to_prw_test.go b/storage/remote/otlptranslator/prometheusremotewrite/metrics_to_prw_test.go
new file mode 100644
index 0000000000..4797daeece
--- /dev/null
+++ b/storage/remote/otlptranslator/prometheusremotewrite/metrics_to_prw_test.go
@@ -0,0 +1,134 @@
+// Copyright 2024 The Prometheus Authors
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// Provenance-includes-location: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/95e8f8fdc2a9dc87230406c9a3cf02be4fd68bea/pkg/translator/prometheusremotewrite/metrics_to_prw_test.go
+// Provenance-includes-license: Apache-2.0
+// Provenance-includes-copyright: Copyright The OpenTelemetry Authors.
+
+package prometheusremotewrite
+
+import (
+	"fmt"
+	"testing"
+	"time"
+
+	"github.com/stretchr/testify/require"
+	"go.opentelemetry.io/collector/pdata/pcommon"
+	"go.opentelemetry.io/collector/pdata/pmetric"
+	"go.opentelemetry.io/collector/pdata/pmetric/pmetricotlp"
+)
+
+func BenchmarkPrometheusConverter_FromMetrics(b *testing.B) {
+	for _, resourceAttributeCount := range []int{0, 5, 50} {
+		b.Run(fmt.Sprintf("resource attribute count: %v", resourceAttributeCount), func(b *testing.B) {
+			for _, histogramCount := range []int{0, 1000} {
+				b.Run(fmt.Sprintf("histogram count: %v", histogramCount), func(b *testing.B) {
+					nonHistogramCounts := []int{0, 1000}
+
+					if resourceAttributeCount == 0 && histogramCount == 0 {
+						// Don't bother running a scenario where we'll generate no series.
+						nonHistogramCounts = []int{1000}
+					}
+
+					for _, nonHistogramCount := range nonHistogramCounts {
+						b.Run(fmt.Sprintf("non-histogram count: %v", nonHistogramCount), func(b *testing.B) {
+							for _, labelsPerMetric := range []int{2, 20} {
+								b.Run(fmt.Sprintf("labels per metric: %v", labelsPerMetric), func(b *testing.B) {
+									for _, exemplarsPerSeries := range []int{0, 5, 10} {
+										b.Run(fmt.Sprintf("exemplars per series: %v", exemplarsPerSeries), func(b *testing.B) {
+											payload := createExportRequest(resourceAttributeCount, histogramCount, nonHistogramCount, labelsPerMetric, exemplarsPerSeries)
+
+											for i := 0; i < b.N; i++ {
+												converter := NewPrometheusConverter()
+												require.NoError(b, converter.FromMetrics(payload.Metrics(), Settings{}))
+												require.NotNil(b, converter.TimeSeries())
+											}
+										})
+									}
+								})
+							}
+						})
+					}
+				})
+			}
+		})
+	}
+}
+
+func createExportRequest(resourceAttributeCount int, histogramCount int, nonHistogramCount int, labelsPerMetric int, exemplarsPerSeries int) pmetricotlp.ExportRequest {
+	request := pmetricotlp.NewExportRequest()
+
+	rm := request.Metrics().ResourceMetrics().AppendEmpty()
+	generateAttributes(rm.Resource().Attributes(), "resource", resourceAttributeCount)
+
+	metrics := rm.ScopeMetrics().AppendEmpty().Metrics()
+	ts := pcommon.NewTimestampFromTime(time.Now())
+
+	for i := 1; i <= histogramCount; i++ {
+		m := metrics.AppendEmpty()
+		m.SetEmptyHistogram()
+		m.SetName(fmt.Sprintf("histogram-%v", i))
+		m.Histogram().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
+		h := m.Histogram().DataPoints().AppendEmpty()
+		h.SetTimestamp(ts)
+
+		// Set 50 samples, 10 each with values 0.5, 1, 2, 4, and 8
+		h.SetCount(50)
+		h.SetSum(155)
+		h.BucketCounts().FromRaw([]uint64{10, 10, 10, 10, 10, 0})
+		h.ExplicitBounds().FromRaw([]float64{.5, 1, 2, 4, 8, 16}) // Bucket boundaries include the upper limit (ie. each sample is on the upper limit of its bucket)
+
+		generateAttributes(h.Attributes(), "series", labelsPerMetric)
+		generateExemplars(h.Exemplars(), exemplarsPerSeries, ts)
+	}
+
+	for i := 1; i <= nonHistogramCount; i++ {
+		m := metrics.AppendEmpty()
+		m.SetEmptySum()
+		m.SetName(fmt.Sprintf("sum-%v", i))
+		m.Sum().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
+		point := m.Sum().DataPoints().AppendEmpty()
+		point.SetTimestamp(ts)
+		point.SetDoubleValue(1.23)
+		generateAttributes(point.Attributes(), "series", labelsPerMetric)
+		generateExemplars(point.Exemplars(), exemplarsPerSeries, ts)
+	}
+
+	for i := 1; i <= nonHistogramCount; i++ {
+		m := metrics.AppendEmpty()
+		m.SetEmptyGauge()
+		m.SetName(fmt.Sprintf("gauge-%v", i))
+		point := m.Gauge().DataPoints().AppendEmpty()
+		point.SetTimestamp(ts)
+		point.SetDoubleValue(1.23)
+		generateAttributes(point.Attributes(), "series", labelsPerMetric)
+		generateExemplars(point.Exemplars(), exemplarsPerSeries, ts)
+	}
+
+	return request
+}
+
+func generateAttributes(m pcommon.Map, prefix string, count int) {
+	for i := 1; i <= count; i++ {
+		m.PutStr(fmt.Sprintf("%v-name-%v", prefix, i), fmt.Sprintf("value-%v", i))
+	}
+}
+
+func generateExemplars(exemplars pmetric.ExemplarSlice, count int, ts pcommon.Timestamp) {
+	for i := 1; i <= count; i++ {
+		e := exemplars.AppendEmpty()
+		e.SetTimestamp(ts)
+		e.SetDoubleValue(2.22)
+		e.SetSpanID(pcommon.SpanID{0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08})
+		e.SetTraceID(pcommon.TraceID{0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f})
+	}
+}