--- title: "AssemblyAI free inference" description: "$50 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for AssemblyAI." canonical_url: "https://freeinferencing.com/provider/assemblyai/" md_url: "https://freeinferencing.com/provider/assemblyai.md" last_updated: "2026-09-19" --- # AssemblyAI > $50 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:** $50.00 once - **API endpoint:** `https://api.assemblyai.com` ## Models mentioned No stable model IDs were recorded in this snapshot. ## Limits and terms ```yaml signup_credit_usd: 50 expiry: none recurrence: false exclusions: - LLM Gateway ``` ## What happens to your prompts? **Not private.** Standard terms allow indefinite retention in some modes and permit training and broad improvement unless excluded or opted out. 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: AssemblyAI async and streaming speech APIs plus LLM Gateway; training opt-out, BAA, EU, TTL, and upstream-model choices materially change handling. prompt_retention: Without a configured TTL or BAA, async transcripts and text prompts can be retained indefinitely; uploaded audio deletion starts after 24 hours and completes within 48 hours. Streaming offers content ZDR only when training is opted out. response_retention: Async transcription artifacts follow the configured TTL, which can be as low as one hour; without TTL or BAA they are indefinite. LLM Gateway content follows customer TTL and upstream-provider rules. ordinary_logging: Transcript metadata is retained for logging and billing even where content ZDR applies; Usage Data can be used broadly for business purposes. model_training: The standard terms permit training and product improvement with Customer Data. Customers can opt out; BAA customers and EU-server use are excluded from AssemblyAI model training. All LLM Gateway upstream providers are configured no-training. product_improvement: Unless excluded or opted out, Customer Data and de-identified derivatives can be used for development, testing, benchmarking, marketing, and model improvement. human_or_operator_access: Retained production and training data can be accessed under security controls for support, model development, safety, and legal purposes; training and production environments are separate. subprocessors_and_routing: LLM Gateway routes to Anthropic, Google, OpenAI, and Bedrock paths with provider-specific retention; OpenAI routes retain abuse logs for 30 days, while named Anthropic and Google routes can provide ZDR. deletion_controls: Customers can set an async TTL down to one hour, delete transcripts by API, opt out of model training, select EU processing, and use eligible Streaming or LLM Gateway ZDR configurations. caveat: "Free/default use should not be assumed private: training is contractually permitted and async transcripts can persist indefinitely until the user selects an opt-out and retention control." agreements: terms_of_service: https://www.assemblyai.com/legal/terms-of-service privacy_policy: https://www.assemblyai.com/legal/privacy-policy data_processing_addendum: https://www.assemblyai.com/legal/data-processing-addendum ``` ## Eligibility ```yaml account_required: true payment_method_required: false ``` ## API compatibility and modalities - **Compatibility:** Assemblyai Rest And Websocket - **Modalities:** Speech To Text, Speech Understanding, Audio Guardrails, Speech / audio, Safety ## Before you build with AssemblyAI ### 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 **Not private** because Standard terms allow indefinite retention in some modes and permit training and broad improvement unless excluded or opted out. 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 - [Free signup](https://support.assemblyai.com/articles/5370767329-can-i-sign-up-for-free): Official Help - [Account billing and free credits](https://www.assemblyai.com/docs/faq/how-to-get-your-api-key): Official Docs - [AssemblyAI Terms of Service](https://www.assemblyai.com/legal/terms-of-service): Official Terms - [AssemblyAI Privacy Policy](https://www.assemblyai.com/legal/privacy-policy): Official Privacy - [AssemblyAI Data Processing Addendum](https://www.assemblyai.com/legal/data-processing-addendum): Official Dpa - [Data retention and model training](https://www.assemblyai.com/docs/data-retention-and-model-training): Official Docs - [PyPI download stats for assemblyai](https://pypistats.org/packages/assemblyai): Package Registry Stats ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.