I was looking at a flame graph of an ingestion workload with @dliappis, and it looks like we parse the JSON representation of the index request twice when a document has both a pipeline and a final pipeline.

It's hard to know how much we would save on this benchmark since not all data streams in this benchmark had both a pipeline and a final pipeline, but the cost of parsing index request into maps of maps via IngestService represented 4.06% of overall CPU time according to the flame graph, so this might not be negligible.
server/src/test/java/org/elasticsearch/ingest/IngestServiceTests.java
return Map.of("test", (factories, tag, description, config) -> {
                    assertThat(counter.compareAndSet(1, 2), is(true));
                    return new FakeProcessor("test", tag, description, ingestDocument -> {});
                });
            }
        };
        
        Client client = mock(Client.class);
        IngestService ingestService = new IngestService(
            mock(ClusterService.class),
            threadPool,
            null,
            null,
            null,
            List.of(testPlugin),
            client
        );
        ingestService.addIngestClusterStateListener(ingestClusterStateListener);
        
        PutPipelineRequest putRequest = new PutPipelineRequest(
            "_id",
            new BytesArray("{\"processors\": [{\"test\" : {}}]}"),
            XContentType.JSON
        );
        ClusterState clusterState = ClusterState.builder(new ClusterName("_name")).build(); 
        ClusterState previousClusterState = clusterState;
        clusterState = executePut(putRequest, clusterState);
        ingestService.applyClusterState(new ClusterChangedEvent("", clusterState, previousClusterState));
        
        assertThat(counter.get(), equalTo(2));