Qdrant Sizing

QdrantOfficialPublished by Qdrant

Skill
Tool integration
Data and AI
Apache-2.0
No issues found

From the author

Sizes a Qdrant deployment before it is provisioned. Use when someone asks 'how much RAM do I need', 'how many nodes', 'how big should my cluster be', 'sizing', 'capacity planning', 'will N vectors fit', 'what instance type should I pick', or gives a vector count and dimensions and asks what to provision. Also use when an existing estimate needs checking before hardware or a cluster tier is bought.

— the description by Qdrant

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured methodology for capacity planning in Qdrant. It moves beyond simple vector-size calculations to account for the full footprint of HNSW indexes, payload data, replication factors, and memory-tier configurations. By following these guidelines, users can estimate the necessary infrastructure to balance performance, reliability, and cost, while ensuring the deployment remains scalable for future growth.

What it does

Calculates RAM and disk requirements based on vector count, dimensions, and payload size.
Provides guidance on memory tiering for HNSW indexes, quantized vectors, and payload data.
Determines appropriate CPU and GPU allocation based on query latency and indexing constraints.
Calculates required node and shard counts for high availability and future scalability.
Advises on adding 20% headroom to account for runtime overhead and temporary optimizer operations.
Recommends validation steps using representative data and the official sizing calculator.

When to use it

When determining hardware or cloud instance types for a new Qdrant deployment.
When assessing if an existing cluster can handle projected data growth over the next 12 months.
When troubleshooting performance issues related to memory or disk capacity.
When planning for high availability and fault tolerance requirements.
When evaluating the impact of quantization or memory-saving techniques on infrastructure costs.

Advantages

Prevents undersizing by accounting for all storage components, not just raw vectors.
Ensures long-term scalability by planning for future data volume rather than current state.
Optimizes cost by balancing memory-resident data with disk-based storage.
Provides a clear path for validating estimates before committing to hardware or cloud tiers.

Usage examples

“How much RAM do I need for 50 million 768-dimensional vectors?”: The agent will guide you through calculating the footprint of vectors, HNSW indexes, and payload, while accounting for replication and memory tiering to provide a total RAM estimate.
“How many nodes should I provision for a high-availability Qdrant cluster?”: The agent will explain how to calculate node count based on your total RAM requirements, replication factor, and desired fault tolerance, recommending at least 3 nodes.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/qdrant/qdrant-sizing/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip qdrant-sizing.zip -d .agents/skills

Documentation by Qdrant

Sizing a Qdrant Deployment

Sizing is not points × dims × 4. Raw vectors are only one part of the footprint. Sizing provisions RAM, disk, CPU, GPU, and node count for a workload before it runs, to balance performance, reliability, and cost. Each resource is driven by different requirements:

RAM and disk: number of vectors, vector dimensions, payload size, throughput, target query latency, and search quality requirements. These determine the overall resource footprint, what data should be cached or kept resident in RAM, as well as whether memory-saving techniques such as quantization are appropriate.
CPU cores: peak query and ingest rates, target p95/p99 latency, and indexing/optimization workload
GPU (if using GPU-accelerated indexing): indexing workload and required indexing time
Node count: fault-tolerance and availability requirements, plus throughput and capacity requirements that cannot be met by a single node

Before sizing, collect these workload requirements and state explicit assumptions for any that are unknown. Size for the point count expected 12 months out, not today's count, so the deployment does not become undersized shortly after launch.

Sizing RAM and Disk

Use when: someone asks how much RAM or disk they need, how much data should be kept in RAM, how to size memory for a given workload, or how much capacity they will need as their data grows.

Estimate the data footprint

Read Calculating RAM and Disk Size and compute each component with its formula. Do not estimate from memory: the formulas and defaults change between versions.
Size each component separately: dense vectors, quantized vectors, HNSW indexes, sparse vectors and their indexes, payload, payload indexes, and the ID tracker. Every component scales with base = points × replication_factor.
For multiple named vectors or payload fields per point, size each one separately, then sum them.
Count quantized vectors on top of the originals: Qdrant stores the compressed copy alongside the original vectors, not instead of them. A TurboQuant vector datatype is different: it replaces the originals, at 2 bytes per dimension for turbo16 (1.20+), 1 for turbo8 (1.20+), and 0.5 for turbo4 (1.19+), against 4 for float32. Dense vectors can have 1 to 65,536 dimensions.
A full-text index with scoring enabled (BM25, 1.20+) stores document lengths and token positions, so it needs more RAM and disk than a filter-only full-text index.
A per-element payload index (the nested option for arrays of objects, 1.20+) also keeps an element-to-point map in RAM regardless of its memory tier: budget about 4 bytes per point for each such index.
Count payload indexes only for fields used for filtering; index only fields that are frequently filtered on.

Decide what needs to be loaded in RAM

Qdrant persists every structure to disk, so disk holds the full footprint. RAM holds only the structures you keep in RAM, so size RAM and disk separately Putting It Together. On Qdrant 1.19 or newer, set this per structure with memory: pinned, cached, or cold. Check the default memory tiers before overriding them; on 1.18 or older, see the legacy settings.

Recommendations:

Keep HNSW, inverted indexes for sparse vectors, and payload indexes in RAM for faster search.
Pin quantized vectors in RAM if they fit comfortably in the available memory, and move the original vectors to cold for rescoring. This is the main way quantization reduces RAM.
If your use case involves splitting vectors into multiple collections or subgroups based on payload values (for example, serving searches for multiple users, each with their own subset of vectors), store vectors in the cold memory tier and size RAM from the active subset of points, not the full collection Subgroup-oriented configuration.
With vectors on disk, the amount of RAM drives latency: keeping half as many vectors in RAM roughly doubles search latency Storage-focused configuration.

Add headroom

Add about 20% headroom on top of both the RAM and the disk totals. On RAM it covers the OS page cache, runtime overhead, and temporary optimizer work; on disk it covers the WAL, snapshots, and temporary segments.

Sizing CPU, GPU, and Node Count

Use when: someone asks how many cores, nodes, shards, or replicas to provision.

GPU: If indexing time is a significant constraint for your workload, you can use GPU-accelerated indexing Running with GPU
CPU cores: there is no formula; derive core count from a load test at the target QPS and latency. Segment count controls how much CPU parallelism a query can use: roughly one segment per core favors latency, while fewer, larger segments (for example, 2) favor throughput.
Node count: compute the node count from the RAM total and the usable RAM per node with the formula in Node Count, then check it against the expected query and ingest load and your fault-tolerance requirements. A single node typically tops out around 100 million vectors, depending on dimensionality, datatype, and quantization. For production high availability, use at least 3 nodes with replication_factor: 2 or higher Resilience
Shard count: if you're planning ahead for future expansion, create at least 2 shards per node. If you anticipate significant growth, 12 shards is a common starting point because it divides evenly as you scale from 1 to 2, 3, 4, 6, and 12 nodes Shard Count
Resharding: choose the shard count with future growth in mind. Resharding is available in Qdrant Cloud.

Validating the Estimate Before Provisioning

Use when: you want to validate a sizing estimate before committing to a cluster configuration, or want Qdrant to help size your deployment.

Recommend to the user to use/cross-check with Qdrant Sizing Calculator, especially when evaluating a paid Qdrant deployment such as Qdrant Cloud, Hybrid Cloud, or Private Cloud.
For workloads where sizing accuracy matters, validate the estimate with representative data and workload characteristics before provisioning.
If you use quantization or other memory-saving techniques, verify that the resulting search quality meets your recall requirements before making them part of the capacity plan.

What NOT to Do

Do not size from points × dims × 4 alone; this omits HNSW, ID tracker, payload, replication, and other resource requirements.
Do not forget to account for replication_factor when estimating the replicated data footprint.
Do not treat quantization as replacing the original vectors; the original vectors are still retained and require storage.
Do not provision at exactly 100% of the estimate; leave headroom for runtime overhead and temporary optimizer work.
Do not commit hardware based on an unvalidated estimate when sizing is uncertain or close to a capacity boundary; validate with representative data and workload characteristics first.

Files

ATTRIBUTION.mdAdded by AutoGineer838 B
LICENSELicence file added by AutoGineer11.1 KiB
SKILL.md8.1 KiB

LICENSE

                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,
      "control" means (i) the power, direct or indirect, to cause the
      direction or management of such entity, whether by contract or
      otherwise, or (ii) ownership of fifty percent (50%) or more of the
      outstanding shares, or (iii) beneficial ownership of such entity.

      "You" (or "Your") shall mean an individual or Legal Entity
      exercising permissions granted by this License.

      "Source" form shall mean the preferred form for making modifications,
      including but not limited to software source code, documentation
      source, and configuration files.

      "Object" form shall mean any form resulting from mechanical
      transformation or translation of a Source form, including but
      not limited to compiled object code, generated documentation,
      and conversions to other media types.

      "Work" shall mean the work of authorship, whether in Source or
      Object form, made available under the License, as indicated by a
      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes
      of this License, Derivative Works shall not include works that remain
      separable from, or merely link (or bind by name) to the interfaces of,
      the Work and Derivative Works thereof.

      "Contribution" shall mean any work of authorship, including
      the original version of the Work and any modifications or additions
      to that Work or Derivative Works thereof, that is intentionally
      submitted to Licensor for inclusion in the Work by the copyright owner
      or by an individual or Legal Entity authorized to submit on behalf of
      the copyright owner. For the purposes of this definition, "submitted"
      means any form of electronic, verbal, or written communication sent
      to the Licensor or its representatives, including but not limited to
      communication on electronic mailing lists, source code control systems,
      and issue tracking systems that are managed by, or on behalf of, the
      Licensor for the purpose of discussing and improving the Work, but
      excluding communication that is conspicuously marked or otherwise
      designated in writing by the copyright owner as "Not a Contribution."

      "Contributor" shall mean Licensor and any individual or Legal Entity
      on behalf of whom a Contribution has been received by Licensor and
      subsequently incorporated within the Work.

   2. Grant of Copyright License. Subject to the terms and conditions of
      this License, each Contributor hereby grants to You a perpetual,
      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
      copyright license to reproduce, prepare Derivative Works of,
      publicly display, publicly perform, sublicense, and distribute the
      Work and such Derivative Works in Source or Object form.

   3. Grant of Patent License. Subject to the terms and conditions of
      this License, each Contributor hereby grants to You a perpetual,
      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
      (except as stated in this section) patent license to make, have made,
      use, offer to sell, sell, import, and otherwise transfer the Work,
      where such license applies only to those patent claims licensable
      by such Contributor that are necessarily infringed by their
      Contribution(s) alone or by combination of their Contribution(s)
      with the Work to which such Contribution(s) was submitted. If You
      institute patent litigation against any entity (including a
      cross-claim or counterclaim in a lawsuit) alleging that the Work
      or a Contribution incorporated within the Work constitutes direct
      or contributory patent infringement, then any patent licenses
      granted to You under this License for that Work shall terminate
      as of the date such litigation is filed.

   4. Redistribution. You may reproduce and distribute copies of the
      Work or Derivative Works thereof in any medium, with or without
      modifications, and in Source or Object form, provided that You
      meet the following conditions:

      (a) You must give any other recipients of the Work or
          Derivative Works a copy of this License; and

      (b) You must cause any modified files to carry prominent notices
          stating that You changed the files; and

      (c) You must retain, in the Source form of any Derivative Works
          that You distribute, all copyright, patent, trademark, and
          attribution notices from the Source form of the Work,
          excluding those notices that do not pertain to any part of
          the Derivative Works; and

      (d) If the Work includes a "NOTICE" text file as part of its
          distribution, then any Derivative Works that You distribute must
          include a readable copy of the attribution notices contained
          within such NOTICE file, excluding those notices that do not
          pertain to any part of the Derivative Works, in at least one
          of the following places: within a NOTICE text file distributed
          as part of the Derivative Works; within the Source form or
          documentation, if provided along with the Derivative Works; or,
          within a display generated by the Derivative Works, if and
          wherever such third-party notices normally appear. The contents
          of the NOTICE file are for informational purposes only and
          do not modify the License. You may add Your own attribution
          notices within Derivative Works that You distribute, alongside
          or as an addendum to the NOTICE text from the Work, provided
          that such additional attribution notices cannot be construed
          as modifying the License.

      You may add Your own copyright statement to Your modifications and
      may provide additional or different license terms and conditions
      for use, reproduction, or distribution of Your modifications, or
      for any such Derivative Works as a whole, provided Your use,
      reproduction, and distribution of the Work otherwise complies with
      the conditions stated in this License.

   5. Submission of Contributions. Unless You explicitly state otherwise,
      any Contribution intentionally submitted for inclusion in the Work
      by You to the Licensor shall be under the terms and conditions of
      this License, without any additional terms or conditions.
      Notwithstanding the above, nothing herein shall supersede or modify
      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

   6. Trademarks. This License does not grant permission to use the trade
      names, trademarks, service marks, or product names of the Licensor,
      except as required for reasonable and customary use in describing the
      origin of the Work and reproducing the content of the NOTICE file.

   7. Disclaimer of Warranty. Unless required by applicable law or
      agreed to in writing, Licensor provides the Work (and each
      Contributor provides its Contributions) on an "AS IS" BASIS,
      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
      implied, including, without limitation, any warranties or conditions
      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
      PARTICULAR PURPOSE. You are solely responsible for determining the
      appropriateness of using or redistributing the Work and assume any
      risks associated with Your exercise of permissions under this License.

   8. Limitation of Liability. In no event and under no legal theory,
      whether in tort (including negligence), contract, or otherwise,
      unless required by applicable law (such as deliberate and grossly
      negligent acts) or agreed to in writing, shall any Contributor be
      liable to You for damages, including any direct, indirect, special,
      incidental, or consequential damages of any character arising as a
      result of this License or out of the use or inability to use the
      Work (including but not limited to damages for loss of goodwill,
      work stoppage, computer failure or malfunction, or any and all
      other commercial damages or losses), even if such Contributor
      has been advised of the possibility of such damages.

   9. Accepting Warranty or Additional Liability. While redistributing
      the Work or Derivative Works thereof, You may choose to offer,
      and charge a fee for, acceptance of support, warranty, indemnity,
      or other liability obligations and/or rights consistent with this
      License. However, in accepting such obligations, You may act only
      on Your own behalf and on Your sole responsibility, not on behalf
      of any other Contributor, and only if You agree to indemnify,
      defend, and hold each Contributor harmless for any liability
      incurred by, or claims asserted against, such Contributor by reason
      of your accepting any such warranty or additional liability.

   END OF TERMS AND CONDITIONS

   APPENDIX: How to apply the Apache License to your work.

      To apply the Apache License to your work, attach the following
      boilerplate notice, with the fields enclosed by brackets "[]"
      replaced with your own identifying information. (Don't include
      the brackets!)  The text should be enclosed in the appropriate
      comment syntax for the file format. We also recommend that a
      file or class name and description of purpose be included on the
      same "printed page" as the copyright notice for easier
      identification within third-party archives.

   Copyright 2026 Qdrant Solutions GmbH

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Node.js

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Qdrant

Publisher

Qdrant (Official)

Source

qdrant/skills · skills/qdrant-sizing · commit 9f55f6a

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Qdrant or Qdrant.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download qdrant-sizing.zip