--- title: "Qdrant Cloud Inference free inference" description: "A recurring no-cost API allowance covering 6 cataloged models." canonical_url: "https://freeinferencing.com/provider/qdrant_cloud_inference/" md_url: "https://freeinferencing.com/provider/qdrant_cloud_inference.md" last_updated: "2026-09-19" --- # Qdrant Cloud Inference > A recurring no-cost API allowance covering 6 cataloged models. ## Classification - **Directory:** Current - **Free access:** Always-free quota - **Status:** Available now - **Confidence:** High - **Payment card:** No - **Account:** Required - **Equivalent paid value:** Not quantifiable ## Models mentioned - `sentence-transformers/all-MiniLM-L6-v2` - `Qdrant/bm25` - `mixedbread-ai/mxbai-embed-large-v1` - `prithivida/Splade_PP_en_v1` - `Qdrant/clip-ViT-B-32-text` - `Qdrant/clip-ViT-B-32-vision` ## Limits and terms ```yaml 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? **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. Privacy is audited separately from price. Review the current governing terms before sending sensitive or regulated data. ## Data governance and agreements ```yaml data_governance: review_status: partial 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. agreements: privacy_policy: https://qdrant.tech/legal/privacy-policy/ cloud_security: https://qdrant.tech/documentation/cloud-security/ ``` ## Eligibility ```yaml account_required: true free_cloud_cluster_required: true payment_method_required: false ``` ## API compatibility and modalities - **Compatibility:** Qdrant REST And GRPC Inference Integrated Into Collection Upsert And Query Operations - **Modalities:** Dense Embeddings, Sparse Embeddings, Late Interaction Embeddings, Multimodal Embeddings, Embeddings, Image / vision - **Geography:** United States For Free Hosted Models ## Before you build with Qdrant Cloud Inference ### Read the classification narrowly This record 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 account and region. “Always-free quota” should be interpreted together with the Current directory placement, High confidence, No payment-card status, and the plan-specific sources below. ### Resolve the live model route The snapshot records 6 model IDs. Match the exact ID against the provider's current catalog before using it in code because zero-price routes, aliases, context limits, and feature support can rotate while an older documentation page remains online. ### Match the quota to the workload shape Translate the allowance into peak requests per minute, input and output tokens, concurrency, retries, and every daily or monthly ceiling that applies to the intended account. The first limit reached by the workload is the practical ceiling. A large token pool can still fail interactive bursts, and a high request limit can still fail long-context work. Include tool calls and retry traffic, test the largest realistic payload, and treat research, experimental, and community access as conditional on their eligibility and fair-use terms. ### Preserve billing and privacy boundaries The recorded payment-card requirement is No, and account access is required. Confirm both in the live signup flow, set provider-side budgets when charges are possible, and observe the balance or usage fields after a complete request. The prompt-handling classification is **Partially private** because 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. Re-read the terms for the exact route and plan before sending sensitive, regulated, or proprietary content. ### Follow the evidence, then re-check it This record links 7 first-party sources covering the offer, catalog, limits, pricing, terms, privacy, or adoption evidence available to the audit. Prefer the newest and most specific governing document or live catalog when sources disagree. A dated finding can become stale even when the page remains online, so retain the source and snapshot that supported the decision and submit a correction when a provider changes a material term. ### Plan fallback without policy drift A fallback should preserve modality, context length, streaming, structured output, tools, safety controls, and data terms, not only API syntax. Decide which errors may retry, cap retry storms, and prevent an exhausted free route from silently switching to a billable model. Rotating aliases and free pools can change behavior without changing the endpoint, so retain the response model field and test at least one substitute route before the primary offer becomes unavailable. ### Monitor the offer as a dependency Capture the model ID, response model, rate-limit headers, usage fields, latency, HTTP status, and provider request identifier. Watch authorization failure, quota exhaustion, catalog removal, policy revision, and balance movement as separate failure modes. Re-check the live catalog and governing sources on a schedule proportionate to the workload's importance, and keep an owner and exit path for any production dependency on volatile free capacity. ### Test one complete request before scaling Start with the smallest permitted request using the exact credential, model ID, endpoint, region, and account type intended for deployment. Record the status, headers, usage fields, response model, latency, and dashboard balance movement. Then exercise an invalid model, quota exhaustion, or rate limit so failure is explicit and cannot silently switch to a paid route. Validate streaming, structured output, and tool calls separately because a free model can expose fewer features than its paid counterpart. Keep a budget ceiling outside the application whenever billing is possible, and do not send sensitive data until the observed route matches the reviewed agreement. ## Primary sources - [Cloud Inference](https://qdrant.tech/documentation/cloud/inference/): Official Docs - [Cloud quickstart](https://qdrant.tech/documentation/cloud/quickstart-cloud/): Official Docs - [Qdrant pricing](https://qdrant.tech/pricing/): Official Pricing - [Qdrant Cloud Inference](https://qdrant.tech/cloud-inference/): Official Product - [Privacy policy](https://qdrant.tech/legal/privacy-policy/): Official Privacy - [Cloud security](https://qdrant.tech/documentation/cloud-security/): Official Security Docs - [About Qdrant](https://qdrant.tech/about-us/): Official Company ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.