--- title: "Clarifai free inference" description: "$5 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for Clarifai." canonical_url: "https://freeinferencing.com/provider/clarifai/" md_url: "https://freeinferencing.com/provider/clarifai.md" last_updated: "2026-09-19" --- # Clarifai > $5 for new accounts; it does not recur. ## Classification - **Directory:** Current - **Free access:** One-time trial - **Status:** Current trial - **Confidence:** High - **Payment card:** Yes - **Account:** Not documented - **Equivalent paid value:** $5.00 once - **API endpoint:** `https://api.clarifai.com` ## Models mentioned No stable model IDs were recorded in this snapshot. ## Limits and terms ```yaml signup_credit_usd: 5 expires_after_days: 30 recurrence: false maximum_welcome_bonuses: 2 payg_requests_per_second_up_to: 100 caveat: The current PAYG account documentation says up to 100 RPS; it is not a guarantee for every model route. ``` ## What happens to your prompts? **Not private.** Inputs and predictions are stored by default and the general terms retain broad service-development rights. 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: reviewed plan_scope: Clarifai cloud platform, inference, stored Inputs, prediction history, and customer-created training; private and Community-shared data differ. prompt_retention: Inputs and resulting predictions are stored by default so customers can review, search, and manage them in the portal; no universal automatic deletion period is published. response_retention: Prediction history is stored by default until the customer manages or deletes it. ordinary_logging: Request counts, compute usage, billing, monitoring, and other non-sensitive operational metadata are logged; more detailed logging features require opt-in according to current product documentation. model_training: Current docs say private data is not used to train Clarifai or other platform models unless the customer explicitly shares inputs and annotations with the Community. product_improvement: Aggregate usage and performance patterns may improve proprietary models without private input data. The general terms also authorize use of Your Content to develop and improve the service, creating a broader contractual permission than the narrower docs describe. human_or_operator_access: Stored private content is treated as confidential by default and is accessible under platform, support, security, and customer-authorized controls; Community sharing makes selected content public to that context. subprocessors_and_routing: Clarifai and its subprocessors host the platform; third-party models can carry separate manufacturer or developer licenses. deletion_controls: Customers can manage stored inputs and prediction history and request account or personal-data deletion, subject to fraud, dispute, fee, and legal-retention exceptions. caveat: There is a material scope tension between the terms' broad service-improvement right and docs' no-private-data-training promise. The audit treats explicit training as opt-in but does not treat private content as contractually excluded from all product improvement. agreements: terms_of_service: https://clarifai.com/company/terms privacy_policy: https://clarifai.com/company/privacy-policy ``` ## Eligibility ```yaml phone_verification_required: true payment_method_required_initially: false payment_method_required_to_recharge: true ``` ## API compatibility and modalities - **Compatibility:** Clarifai Native, OpenAI Compatible - **Modalities:** Model inference ## Before you build with Clarifai ### 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. “One-time trial” should be interpreted together with the Current directory placement, High confidence, Yes payment-card status, and the plan-specific sources below. ### Resolve the live model route No stable model ID is recorded. Resolve the current machine-readable ID, endpoint, authentication method, and request shape from the provider's live documentation before writing fixed production configuration. ### 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 Yes, and account access is not documented. 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 **Not private** because Inputs and predictions are stored by default and the general terms retain broad service-development rights. 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 10 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 - [Account billing](https://docs.clarifai.com/control/account-billing/): Official Docs - [Inference](https://docs.clarifai.com/compute/inference/): Official Docs - [Rate limits](https://docs.clarifai.com/resources/api-overview/rate-limits/): Official Docs - [Community plan retirement](https://docs.clarifai.com/product-updates/changelog/release121/): Official Changelog - [Clarifai Terms of Service](https://clarifai.com/company/terms): Official Terms - [Clarifai Data Privacy Policy](https://clarifai.com/company/privacy-policy): Official Privacy - [Clarifai Data Privacy and Security](https://docs.clarifai.com/resources/privacy-security/): Official Docs - [Clarifai Inputs Manager](https://docs.clarifai.com/create/inputs/): Official Docs - [Clarifai press release with About Clarifai boilerplate (1.5M+ models built, 500,000+ users, 170 countries), 2025-12-01](https://www.prnewswire.com/news-releases/clarifai-selected-inference-provider-for-arcee-ais-new-trinity-family-of-us-built-open-weight-models-302629285.html): Company Press Release - [PyPI download stats for the official clarifai package](https://pypistats.org/api/packages/clarifai/recent): Package Registry Stats ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.