​ How it works

When a search query is slower than expected, it can be difficult to tell which part of the pipeline is responsible. The showPerformanceDetails parameter returns per-stage timing information so you can pinpoint bottlenecks without guesswork.

​ How it works

Set showPerformanceDetails to true in any search request. Meilisearch will include a performanceDetails object in the response, breaking down how much time each stage of the search pipeline consumed. This parameter is supported on all search routes:

• POST /indexes/{indexUid}/search
• GET /indexes/{indexUid}/search
• POST /multi-search
• POST /indexes/{indexUid}/similar
• GET /indexes/{indexUid}/similar

​ Basic usage

Add showPerformanceDetails to a standard search request:

curl \
  -X POST 'MEILISEARCH_URL/indexes/movies/search' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "q": "glass",
    "showPerformanceDetails": true
  }'

The response includes the usual search results along with a performanceDetails object:

{
  "hits": [
    { "id": 1, "title": "Glass Onion" }
  ],
  "query": "glass",
  "processingTimeMs": 4,
  "performanceDetails": {
    "wait in queue": "295.29µs",
    "search > tokenize query": "436.67µs",
    "search > evaluate query": "649.00µs",
    "search > keyword ranking": "515.71µs",
    "search > format": "288.54µs",
    "search": "3.56ms"
  }
}

​ Understanding performance stages

Each key in performanceDetails represents a stage of the search pipeline. Stage names are hierarchical, using > as a separator (e.g., search > keyword ranking).

​ Top-level stages

​ Sub-stages

These appear as children of the stages. Not all stages appear in every query; Meilisearch only reports stages that were actually executed.

​ Federated search stages

When using showPerformanceDetails at the federation level, you see these stages instead:

​ Multi-search

In multi-search requests, set showPerformanceDetails on each individual query that you want to profile:

curl \
  -X POST 'MEILISEARCH_URL/multi-search' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "queries": [
      {
        "indexUid": "movies",
        "q": "glass",
        "showPerformanceDetails": true
      },
      {
        "indexUid": "actors",
        "q": "samuel",
        "showPerformanceDetails": true
      }
    ]
  }'

Each result in the response includes its own performanceDetails, letting you compare timing across indexes and queries.

​ Federated search

For federated multi-search, set showPerformanceDetails in the federation object to get timing details for the combined search:

curl \
  -X POST 'MEILISEARCH_URL/multi-search' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "federation": {
      "showPerformanceDetails": true
    },
    "queries": [
      { "indexUid": "movies", "q": "glass" },
      { "indexUid": "books", "q": "glass" }
    ]
  }'

​ Similar documents

The similar documents endpoint also supports showPerformanceDetails:

curl \
  -X POST 'MEILISEARCH_URL/indexes/movies/similar' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "id": "143",
    "showPerformanceDetails": true
  }'

​ Practical tips

​ Identify the bottleneck

Look for the stage with the highest duration. Common patterns:

• High wait in queue: your instance is overloaded with concurrent searches. Scale your hardware or reduce query volume.
• High evaluate filter: complex filters expressions or too many filterable attributes. Use granular filterable attributes to disable unused filter features.
• High evaluate query: complex query containing a lot of words or matching a lot of synonyms, generating a complex query tree that is expensive to evaluate. Add stop words, reduce synonyms cardinality.
• High keyword ranking: the query necessitates a lot of iterations in the ranking rules to retrieve the requested amount of documents, reduce the offset and limit parameters, limit searchable attributes, or lower maxTotalHits.
• High embed query: your embedder is slow. Consider switching to a faster model, using a local embedder for search with composite embedders, or caching embeddings.
• High facet distribution: too many faceted attributes or high maxValuesPerFacet. Lower it to the number of facet values you actually display.
• High format: large attributesToRetrieve, attributesToHighlight, or attributesToCrop. Reduce to only the fields your UI needs.
• High wait for remote results: network latency to remote instances. Check network connectivity or colocate instances.

​ Compare before and after

Use showPerformanceDetails before and after configuration changes (adding stop words, adjusting searchable attributes, modifying the search cutoff) to measure the impact of each optimization.

​ Disable in production

Collecting performance details adds a small amount of overhead to each search request. Use this parameter for debugging and profiling, then remove it from production queries.

Performance tuning

Optimize search speed and relevancy for large datasets

Ranking pipeline

Understand how Meilisearch ranks search results

Configure search cutoff

Set time limits to guarantee consistent response times

Search API reference

Full API reference for the search endpoint