Qdrant Cloud Inference
A recurring no-cost API allowance covering 6 cataloged models.
Models mentioned
sentence-transformers/all-MiniLM-L6-v2Qdrant/bm25mixedbread-ai/mxbai-embed-large-v1prithivida/Splade_PP_en_v1Qdrant/clip-ViT-B-32-textQdrant/clip-ViT-B-32-visionEquivalent paid value
How this was valued: The published allowance or a defensible paid comparison is not precise enough to calculate.
Qdrant documents selected zero-price hosted models without a finite token cap, while the exact current free set is authenticated and has no like-for-like paid unit for a bounded value calculation.
Limits and terms
- Zero Price Models
- Several selected hosted models are documented as completely free with no token limit.
- Exact Free Catalog
- Dashboard-only; models marked "Cost: Free" are authoritative.
- Caveat
- Paid-cluster monthly inference allowances and paid hosted models are separate from this record.
What happens to your prompts?
Qdrant limits Cloud data use to service delivery and support, but the inference-specific content-retention boundary is not fully documented and free hosted models run in the United States.
- Plan Scope
- Qdrant Cloud Inference on a free Cloud cluster using Qdrant-hosted models.
- Prompt Retention
- Qdrant says Cloud customer input data is used to provide and support the service, but it does not publish an inference-specific content TTL for text or images submitted for embedding.
- Response Retention
- Generated vectors are written to the customer's Qdrant collection by design and persist until the customer deletes them; transient inference-response retention outside the collection is not separately documented.
- Ordinary Logging
- Qdrant documents log-file processing including IP and service metadata, generally retained for up to 90 days; the boundary between metadata and inference payloads is not explicit.
- Model Training
- No affirmative right to train foundation models on Cloud inference content was found, but the public policy is not a plan-specific no-training commitment.
- Product Improvement
- Aggregate and de-identified service analytics may be used for business and product operations; content-level improvement use is not clearly described.
- Human Or Operator Access
- Authorized personnel may access customer data for support, security, legal, and service operations under Qdrant's Cloud controls.
- Subprocessors And Routing
- Free Qdrant-hosted inference models run in the United States; Qdrant's listed Cloud infrastructure and subprocessors can participate in service delivery.
- Deletion Controls
- Customers control vectors and collections and can delete them; no separate per-inference transient-content deletion control or TTL is published.
- Caveat
- Free hosted-model geography and an incomplete inference-specific retention boundary prevent a private classification even though the general Cloud policy limits business use of customer input data.
Governing documents
- Privacy Policy
- https://qdrant.tech/legal/privacy-policy/
- Cloud Security
- https://qdrant.tech/documentation/cloud-security/
Eligibility
- Account Required
- Yes
- Free Cloud Cluster Required
- Yes
- Payment Method Required
- No
Primary sources
Before you build with Qdrant Cloud Inference
Read the classification narrowly
This record has current first-party evidence for some zero-cost hosted inference. The label describes the bounded offer supported by evidence on 2026-09-19; it does not guarantee permanence, production suitability, uptime, latency, model quality, or access from every region.
Resolve the live model route
This snapshot records 6 model IDs. Match the exact ID against the provider's live catalog before using it in code; zero-price routes and aliases can rotate while an older documentation page remains online. No stable base endpoint is published in this record, so use the linked provider documentation to identify the current request URL and protocol.
Confirm account and billing boundaries
An account is required, so public catalog evidence cannot by itself prove the limits, balance, or billing behavior attached to your workspace. The reviewed evidence explicitly says no payment card is required. Re-check the signup flow because eligibility and billing controls can change after the snapshot. The equivalent paid value shown here prices a documented allowance where possible; it is not cash, guaranteed savings, or protection from overage.
Re-read the prompt policy for your plan
This record classifies the reviewed handling as “Partially private”: Qdrant limits Cloud data use to service delivery and support, but the inference-specific content-retention boundary is not fully documented and free hosted models run in the United States. Provider policies can distinguish free, paid, enterprise, opted-in, and feature-specific traffic, so verify the governing terms for the exact account and route that will receive your data.
Follow the evidence, then re-check it
The record links 7 first-party sources covering the offer, catalog, limits, pricing, terms, privacy, or adoption evidence available to the audit. Prefer the newest governing document or live catalog when sources disagree, and submit a correction when a provider changes a material term.
Match the quota to the workload shape
Translate the published allowance into the traffic pattern you actually expect instead of comparing headline totals alone. A daily token pool can look generous while a low requests-per-minute or concurrency ceiling blocks interactive bursts; a high request limit can still fail a long-context job when input, output, or per-request tokens are capped. Separate prompt tokens from generated tokens, include retries and tool calls, and test the largest realistic payload. If the provider documents more than one limit window, the tightest window at your peak load is the practical ceiling. Research, experimental, and community access can also carry eligibility or fair-use constraints that cannot be modeled as a simple number.
Plan fallback without changing the rules
A fallback should preserve more than API syntax. Confirm that the substitute route supports the required modality, context length, streaming behavior, structured output, tools, and safety controls, then compare its prompt-retention and training terms. An OpenAI-compatible request shape does not make providers operationally or contractually equivalent. Decide which errors may trigger a retry, cap retry storms, and prevent an exhausted free route from silently switching to a billable model. If deterministic output matters, record the model revision and sampling settings; rotating aliases and free-model pools can change behavior even when the endpoint remains available.
Monitor the offer as a dependency
Capture the model ID, response model field, rate-limit headers, usage fields, latency, HTTP status, and any provider request identifier for each test. Watch for authorization failures, quota exhaustion, catalog removal, policy revisions, and dashboard balance changes as separate failure modes. Re-check the provider’s live catalog and governing pages on a schedule proportionate to the workload’s importance, and keep the dated sources that supported your decision. Free capacity is especially suitable for prototypes, evaluations, fallbacks, and bounded workloads when the application can tolerate change; a production dependency still needs observability, an exit path, and an owner responsible for re-verification.
Test one complete request before scaling
Start with the smallest permitted request using the exact credential, model ID, endpoint, and account type you intend to deploy. Record the HTTP status, response headers, usage fields, latency, and any dashboard balance change. Then exercise the failure path: an invalid model, an exhausted quota, or a rate-limit response should fail clearly without silently switching to a paid route. If the provider supports streaming or tool calls, validate those features separately because a free model can expose a narrower capability set than its paid counterpart. Keep a budget ceiling outside the application whenever billing is possible, and avoid sending sensitive data until the observed route matches the reviewed data agreement.