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/internalClusterTest/java/org/elasticsearch/index/FinalPipelineIT.java
/*
 * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
 * or more contributor license agreements. Licensed under the Elastic License
 * 2.0 and the Server Side Public License, v 1; you may not use this file except
 * in compliance with, at your election, the Elastic License 2.0 or the Server
 * Side Public License, v 1.
 */
package org.elasticsearch.index;
import org.elasticsearch.action.get.GetRequestBuilder;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.action.index.IndexRequestBuilder;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.ingest.DeletePipelineRequest;
import org.elasticsearch.action.ingest.GetPipelineRequest;
import org.elasticsearch.action.ingest.GetPipelineResponse;
import org.elasticsearch.action.ingest.PutPipelineRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.support.WriteRequest;
import org.elasticsearch.client.internal.Client;
import org.elasticsearch.cluster.metadata.IndexNameExpressionResolver;
import org.elasticsearch.cluster.routing.allocation.AllocationService;
import org.elasticsearch.cluster.service.ClusterService;
import org.elasticsearch.common.bytes.BytesArray;
import org.elasticsearch.common.bytes.BytesReference;
import org.elasticsearch.common.io.stream.NamedWriteableRegistry;