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
@SuppressWarnings("unchecked")
        BiConsumer<Integer, Exception> failureHandler = mock(BiConsumer.class);
        @SuppressWarnings("unchecked")
        final BiConsumer<Thread, Exception> completionHandler = mock(BiConsumer.class);
        ingestService.executeBulkRequest(
            bulkRequest.numberOfActions(),
            bulkRequest.requests(),
            indexReq -> {},
            failureHandler,
            completionHandler,
            Names.WRITE
        );
        verify(failureHandler, times(1)).accept(
            argThat(item -> item == 2),
            argThat(iae -> "pipeline with id [does_not_exist] does not exist".equals(iae.getMessage()))
        );
        verify(completionHandler, times(1)).accept(Thread.currentThread(), null);
    }
    public void testExecuteSuccess() {
        IngestService ingestService = createWithProcessors(
            Map.of("mock", (factories, tag, description, config) -> mockCompoundProcessor())
        );
        PutPipelineRequest putRequest = new PutPipelineRequest(
            "_id",
            new BytesArray("{\"processors\": [{\"mock\" : {}}]}"),
            XContentType.JSON
        );
        ClusterState clusterState = ClusterState.builder(new ClusterName("_name")).build(); 
        ClusterState previousClusterState = clusterState;
        clusterState = executePut(putRequest, clusterState);