--- title: "GroqCloud free inference" description: "A recurring no-cost API allowance covering 13 cataloged models." canonical_url: "https://freeinferencing.com/provider/groqcloud/" md_url: "https://freeinferencing.com/provider/groqcloud.md" last_updated: "2026-09-19" --- # GroqCloud > A recurring no-cost API allowance covering 13 cataloged models. ## Classification - **Directory:** Current - **Free access:** Always-free quota - **Status:** Available now - **Confidence:** High - **Payment card:** No - **Account:** Required - **Equivalent paid value:** At least $94.55/mo - **API endpoint:** `https://api.groq.com/openai/v1` ## Models mentioned - `canopylabs/orpheus-arabic-saudi` - `canopylabs/orpheus-v1-english` - `groq/compound` - `groq/compound-mini` - `meta-llama/llama-prompt-guard-2-22m` - `meta-llama/llama-prompt-guard-2-86m` - `openai/gpt-oss-120b` - `openai/gpt-oss-20b` - `openai/gpt-oss-safeguard-20b` - `qwen/qwen3.6-27b` - `qwen/qwen3.8-27b` - `whisper-large-v3` - `whisper-large-v3-turbo` ## Limits and terms ```yaml scope: organization caveat: The signed-in organization Limits page is authoritative if it differs from this public-table snapshot. ``` ## What happens to your prompts? **Private.** Inputs and outputs are not retained by default or used for training without permission; limited abuse and feature-specific retention exceptions remain. 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: GroqCloud inference and related API features; offline negotiated terms may supersede the online agreement. prompt_retention: Inference inputs and outputs are not retained by default. Reliability or abuse logs may retain them up to 30 days; batch files are retained up to 30 days and fine-tuning data until deleted. response_retention: Same policy as prompts and feature state. ordinary_logging: Usage metadata is always retained and excludes customer inputs and outputs. model_training: Groq is not permitted to train or fine-tune models on inputs or outputs without explicit customer permission or instruction. product_improvement: Customer data use is limited to providing the service, customer instructions, law, reliable operation, and acceptable-use enforcement under the current agreement. human_or_operator_access: Access may occur as needed for reliable operation, abuse investigation, legal compliance, or customer-instructed features; zero-data-retention controls restrict reliability and abuse access. subprocessors_and_routing: Groq affiliates, subprocessors, and contractors receive limited rights needed to deliver the service; third-party model terms may also apply. deletion_controls: All customers may enable zero data retention. The agreement calls for deletion of customer data within 30 days after termination, subject to documented or legal exceptions. caveat: Zero data retention disables features that require stored application state; regional and offline agreements may differ. agreements: services_agreement: https://console.groq.com/docs/legal/services-agreement privacy_policy: https://groq.com/privacy-policy acceptable_use_policy: https://console.groq.com/docs/legal/ai-policy data_processing_addendum: https://console.groq.com/docs/legal/customer-data-processing-addendum ``` ## Eligibility ```yaml account_required: true payment_method_required: false ``` ## API compatibility and modalities - **Compatibility:** OpenAI Chat Completions, OpenAI Responses, Audio Transcriptions, Audio Translations - **Modalities:** Text generation, Speech / audio, Safety ## Before you build with GroqCloud ### 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 13 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 **Private** because Inputs and outputs are not retained by default or used for training without permission; limited abuse and feature-specific retention exceptions remain. 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 12 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 - [Rate limits](https://console.groq.com/docs/rate-limits): Official Docs - [Billing FAQ](https://console.groq.com/docs/billing-faqs): Official Docs - [Models](https://console.groq.com/docs/models): Official Docs - [GroqCloud demand announcement](https://groq.com/newsroom/demand-for-real-time-ai-inference-from-groq-accelerates-week-over-week): Announcement - [Groq Services Agreement](https://console.groq.com/docs/legal/services-agreement): Official Terms - [Privacy Policy](https://groq.com/privacy-policy): Official Privacy - [Acceptable Use and Responsible AI Policy](https://console.groq.com/docs/legal/ai-policy): Official Aup - [Customer Data Processing Addendum](https://console.groq.com/docs/legal/customer-data-processing-addendum): Official Dpa - [Your Data in GroqCloud](https://console.groq.com/docs/your-data): Official Docs - [Groq raises $650M and serves more than five million developers (2026-06-22)](https://groq.com/newsroom/groq-raises-usd650m-to-scale-its-ai-inference-cloud-business): Official Press Release - [1 million developers on GroqCloud milestone (2025-03)](https://groq.com/blog/thank-you-1m-developers-building-with-groqcloud): Official Adoption - [PyPI download stats for groq](https://pypistats.org/packages/groq): Package Registry Stats ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.