---
name: Qdrant Performance Optimization
slug: qdrant-performance-optimization
category: DevOps
description: Qdrant Performance Optimization routes users to sub-skills for search speed, indexing performance, and memory usage tuning. Use it when planning configuration or capacity changes to improve speed and efficiency.
github: "https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization"
language: Python
stars: 230
forks: 28
install: "npx degit https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization ~/.claude/skills/qdrant-performance-optimization"
installs_to: ~/.claude/skills/qdrant-performance-optimization
source_path: skills/qdrant-performance-optimization/SKILL.md
collection_size: 25
category_size: 868
collection_url: "https://dirskills.com/collections/qdrant/skills"
added: 2026-09-03T06:04:23.999Z
last_synced: 2026-09-03T06:04:23.999Z
canonical_url: "https://dirskills.com/skills/qdrant-performance-optimization"
---

# Qdrant Performance Optimization

Qdrant Performance Optimization routes users to sub-skills for search speed, indexing performance, and memory usage tuning. Use it when planning configuration or capacity changes to improve speed and efficiency.

**Install:**

```bash
npx degit https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization ~/.claude/skills/qdrant-performance-optimization
```

## README

# 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 says | Read |
|---|---|
| Filtered queries much slower than unfiltered | `search-speed-optimization/SKILL.md` |
| Low QPS, cannot handle the query load | `search-speed-optimization/SKILL.md` |
| Individual queries take too long to return | `search-speed-optimization/SKILL.md` |
| Index build or HNSW build takes too long, vector upload is slow | `indexing-performance-optimization/SKILL.md` |
| Collection stays yellow, optimizer stuck or runs for a long time | `indexing-performance-optimization/SKILL.md` |
| Bulk upsert of vectors is slow | `indexing-performance-optimization/SKILL.md` |
| RAM usage too high, out-of-memory crashes | `memory-usage-optimization/SKILL.md` |
| Want to fit a larger dataset on the same hardware | `memory-usage-optimization/SKILL.md` |
| Reducing cost by moving data to disk | `memory-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.