qdrant-performance-optimization

v2026.09.24

Navigation hub linking sub-skills for proactive Qdrant tuning: search speed, indexing performance, and memory usage optimization. Use when planning configuration or capacity changes to improve speed and efficiency. For diagnosing an active production slowdown or analyzing live metrics, use qdrant-monitoring instead.

GitHub
Install command
npx skhub add qdrant/qdrant-performance-optimization
Markdown
SKILL.md

Qdrant Performance Optimization

Route first, then answer. Match the user's symptom in the table, Read that file, and answer from it. Do not answer from this page alone: it contains routing only, not the guidance. If two rows match, read both.

The user saysRead
Filtered queries much slower than unfilteredsearch-speed-optimization/SKILL.md
Low QPS, cannot handle the query loadsearch-speed-optimization/SKILL.md
Individual queries take too long to returnsearch-speed-optimization/SKILL.md
Index build or HNSW build takes too long, vector upload is slowindexing-performance-optimization/SKILL.md
Collection stays yellow, optimizer stuck or runs for a long timeindexing-performance-optimization/SKILL.md
Bulk upsert of vectors is slowindexing-performance-optimization/SKILL.md
RAM usage too high, out-of-memory crashesmemory-usage-optimization/SKILL.md
Want to fit a larger dataset on the same hardwarememory-usage-optimization/SKILL.md
Reducing cost by moving data to diskmemory-usage-optimization/SKILL.md

Latency and throughput pull opposite ways on segment count. For latency, increase segments toward the CPU core count (default_segment_number: 16). For throughput, use fewer and larger segments (default_segment_number: 2). Applying the wrong direction makes the reported problem worse.

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Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

Apache-2.0

Source path

skills/qdrant-performance-optimization

Default branch

main

Latest commit

6a03d0c

Tree SHA

9bdc29b