Qdrant Pricing (2026)

Pure usage-based billing calculated hourly across vCPU, memory, storage, backups, and inference tokens — you're paying for infrastructure consumption, not seats. The value metric is compute and data scale, which maps tightly to how vector search workloads actually grow.

5 plans usage-based Free plan
Free Tier
$0/mo
Standard Tier
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Premium Tier
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Hybrid Cloud
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Private Cloud
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Verified Jul 25, 2026 Official pricing page
Screenshot of Qdrant's pricing page showing its plans and prices
Their pricing page, captured Jul 25, 2026

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Free Tier

$0/mo
  • Single Node Cluster
  • 0.5 vCPU / 1GB RAM/ 4 GB Disk.
  • Free Cloud Inference With Selected Models

Standard Tier

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  • Dedicated Resources
  • Flexible Vertical and Horizontal Scaling
  • Highly Available Setups
  • Backup & Disaster Recovery
  • Free Tokens for Paid Inference Models
  • 99.5% Uptime SLA

Premium Tier

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  • SSO
  • Private VPC Links
  • 99.9% Uptime SLA
  • Extra Support

Hybrid Cloud

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  • Local Data Residency
  • Regulated Workloads
  • Easy Operations in Your Own Cloud
  • Data Stays in Your Network
  • Fully Managed Through Qdrant Cloud
  • Production-Grade Uptime

Private Cloud

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  • Large Enterprises
  • Sensitive Workloads
  • Air-Gapped Setups
  • Custom SLAs
  • Full Isolation

AI Pricing Analysis

Pricing Model

Pure usage-based billing calculated hourly across vCPU, memory, storage, backups, and inference tokens — you're paying for infrastructure consumption, not seats. The value metric is compute and data scale, which maps tightly to how vector search workloads actually grow.

Tier Strategy

The free tier is a sandbox for developers kicking the tires; Standard is for teams running real workloads who want flexibility without a contract; Premium targets orgs that need SLAs and support, signaled by the minimum spend requirement. The upgrade trigger is almost always production readiness — when downtime costs money or compliance enters the picture, free stops being an option.

Competitive Positioning

Qdrant is positioning as a serious infrastructure-grade alternative to Pinecone, sitting in the mid-to-premium range for managed vector DBs but with the added credibility of Hybrid and Private Cloud options that pure SaaS competitors can't match. They're clearly going after enterprise teams that want control over where their data lives, not just the fastest path to an API key.

Growth Lever

Expansion is entirely consumption-driven — as vector collections grow and query volume scales, the hourly meter runs faster. The real unlock behind the paywall is deployment flexibility: Hybrid and Private Cloud are the wedge for regulated industries and enterprises that can't put sensitive embeddings in a shared cloud environment.

Qdrant Pricing FAQ

How much does Qdrant cost?
Pricing is custom — you'll need to talk to their sales team for a quote.
Is there a free plan?
Yes. The "Free Tier" plan is free forever, not just a trial. You get single node cluster, 0.5 vcpu / 1gb ram/ 4 gb disk., free cloud inference with selected models. It's enough to evaluate the product before upgrading.
Can I try it before paying?
There's no trial per se, but the free plan lets you use the product indefinitely with some limits.
How does the pricing work?
Pure usage-based billing calculated hourly across vCPU, memory, storage, backups, and inference tokens — you're paying for infrastructure consumption, not seats. The value metric is compute and data scale, which maps tightly to how vector search workloads actually grow.
Which plan makes sense for me?
The free tier is a sandbox for developers kicking the tires; Standard is for teams running real workloads who want flexibility without a contract; Premium targets orgs that need SLAs and support, signaled by the minimum spend requirement. The upgrade trigger is almost always production readiness — when downtime costs money or compliance enters the picture, free stops being an option.

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