--- title: "AI21 Studio free inference" description: "$10 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for AI21 Studio." canonical_url: "https://freeinferencing.com/provider/ai21_studio/" md_url: "https://freeinferencing.com/provider/ai21_studio.md" last_updated: "2026-09-19" --- # AI21 Studio > $10 for new accounts; it does not recur. ## Classification - **Directory:** Current - **Free access:** One-time trial - **Status:** Current trial - **Confidence:** High - **Payment card:** No - **Account:** Required - **Equivalent paid value:** $10.00 once - **API endpoint:** `https://api.ai21.com/studio/v1` ## Models mentioned No stable model IDs were recorded in this snapshot. ## Limits and terms ```yaml signup_credit_usd: 10 expires_after_months: 3 recurrence: false coverage: API, SDK, and playground usage. ``` ## What happens to your prompts? **Partially private.** Default retention and training treatment are not clear; stronger traceless operation requires explicit configuration. 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: AI21 Studio and Models API; negotiated Traceless Operations has stronger handling than default access. prompt_retention: The model terms say the service is not intended as storage, but no default public retention maximum was verified. Traceless Operations can disable content retention when explicitly configured. response_retention: Same unresolved default; Traceless Operations applies only when contracted/configured. ordinary_logging: Usage and operational metadata may be retained; the public terms do not publish a complete default content-log TTL. model_training: No sufficiently clear plan-specific default training statement was found in the reviewed public model terms. product_improvement: The agreement permits service operation and improvement uses subject to customer terms; exact content scope remains unclear. human_or_operator_access: Support, security, and legal workflows may permit access; Traceless Operations is the documented stronger control. subprocessors_and_routing: AI21 and its cloud/service subprocessors process requests. deletion_controls: Traceless Operations supports a retain=false mode; default account deletion does not establish immediate request-content deletion. caveat: Do not infer Traceless Operations for free Studio access; it is a separately described negotiated/configured mode. agreements: terms_of_service: https://www.ai21.com/terms-policies/terms-of-use/ privacy_policy: https://www.ai21.com/terms-policies/privacy-policy/ service_specific_terms: https://lp.ai21.com/hubfs/resources/AI21-Models-Terms-of-Service.pdf ``` ## Eligibility ```yaml account_required: true payment_method_required_initially: false ``` ## API compatibility and modalities - **Compatibility:** Ai21 Rest - **Modalities:** Model inference ## Before you build with AI21 Studio ### 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, No 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 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 Default retention and training treatment are not clear; stronger traceless operation requires explicit configuration. 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 - [Usage and cost](https://docs.ai21.com/docs/usage-cost): Official Pricing - [Model availability across platforms](https://docs.ai21.com/docs/model-availability-across-platforms): Official Docs - [AI21 Terms of Use](https://www.ai21.com/terms-policies/terms-of-use/): Official Terms - [AI21 Privacy Policy](https://www.ai21.com/terms-policies/privacy-policy/): Official Privacy - [AI21 Models Terms of Service](https://lp.ai21.com/hubfs/resources/AI21-Models-Terms-of-Service.pdf): Official Terms - [PyPI download stats for ai21](https://pypistats.org/packages/ai21): Package Registry Stats - [Amazon Bedrock models at a glance listing the AI21 Labs Jamba model family](https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards.html): Official Docs ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.