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
public IngestDocument execute(final IngestDocument ingestDocument) {
                throw new AssertionError("Document should have been dropped but reached this processor");
            }
            @Override
            public String getType() {
                return null;
            }
            @Override
            public String getTag() {
                return null;
            }
            @Override
            public String getDescription() {
                return null;
            }
        });
        IngestService ingestService = createWithProcessors(factories);
        PutPipelineRequest putRequest = new PutPipelineRequest(
            "_id",
            new BytesArray("{\"processors\": [{\"drop\" : {}}, {\"mock\" : {}}]}"),
            XContentType.JSON
        );
        ClusterState clusterState = ClusterState.builder(new ClusterName("_name")).build(); 
        ClusterState previousClusterState = clusterState;
        clusterState = executePut(putRequest, clusterState);
        ingestService.applyClusterState(new ClusterChangedEvent("", clusterState, previousClusterState));
        BulkRequest bulkRequest = new BulkRequest();
        final IndexRequest indexRequest1 = new IndexRequest("_index").id("_id1")
            .source(Map.of())
            .setPipeline("_none")