--- title: "Cerebras Inference free inference" description: "$5 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for Cerebras Inference." canonical_url: "https://freeinferencing.com/provider/cerebras_inference/" md_url: "https://freeinferencing.com/provider/cerebras_inference.md" last_updated: "2026-09-19" --- # Cerebras Inference > $5 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:** $5.00 once - **API endpoint:** `https://api.cerebras.ai/v1` ## Models mentioned - `gpt-oss-120b` - `qwen-3.8-27b` ## Limits and terms ```yaml signup_credit_usd: 5 expiry: not_public recurrence: false caveat: The current pricing page confirms $5 account credits but does not publish an expiry or card requirement. Free-plan rate-limit tables remain model-specific and may conflict with deprecation notices. ``` ## What happens to your prompts? **Private.** Cerebras states inference inputs and outputs are not retained or used for content-based training or improvement. 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: Cerebras Cloud inference, training, and chatbot services under its public terms and Cloud privacy policy. prompt_retention: Cerebras states it does not retain inputs and outputs associated with inference, training, or chatbot services. response_retention: Same non-retention statement as prompts. ordinary_logging: Service logs are retained only while necessary to provide the services; account and personal data follow purpose-based retention plus legal, dispute, and enforcement exceptions. model_training: No ordinary retained inputs or outputs are available for model training, and no inference-content training right is disclosed in the reviewed documents. product_improvement: Non-content service data and user feedback may support operations and improvement; the privacy policy does not authorize using inference payloads for improvement. human_or_operator_access: The non-retention policy limits stored access, but transient processing, security operations, and legal obligations remain; no separate zero-operator-access promise is published. subprocessors_and_routing: Cerebras and its service providers process data under the privacy policy; public documentation does not describe inference as a gateway to changing external model providers. deletion_controls: Inference content is not retained. Other personal data can be subject to privacy-right requests and is deleted or aggregated when no longer necessary, subject to legal exceptions. caveat: The policy gives no precise maximum for service logs and does not call the design zero operator access. Non-retention of payloads is a first-party policy statement. agreements: terms_of_service: https://www.cerebras.ai/terms-of-service privacy_policy: https://cloud.cerebras.ai/privacy ``` ## Eligibility ```yaml account_required: true verified_payment_method_required: not_explicitly_documented ``` ## API compatibility and modalities - **Compatibility:** OpenAI Compatible - **Modalities:** Model inference ## Before you build with Cerebras 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. “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 The snapshot records 2 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 Cerebras states inference inputs and outputs are not retained or used for content-based training or improvement. 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 8 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 - [Cerebras Inference pricing and account credit](https://www.cerebras.ai/pricing): Official Pricing - [Current free-plan rate limits](https://inference-docs.cerebras.ai/support/rate-limits): Official Docs - [Inference launch](https://www.cerebras.ai/blog/introducing-cerebras-inference-ai-at-instant-speed): Official Announcement - [Cerebras Terms of Service](https://www.cerebras.ai/terms-of-service): Official Terms - [Cerebras Cloud Privacy Policy](https://cloud.cerebras.ai/privacy): Official Privacy - [Cerebras Policies](https://www.cerebras.ai/policies): Official Legal - [Cerebras Series G announcement (#1 inference provider on Hugging Face with over 5 million monthly requests), 2025-09-30](https://www.cerebras.ai/press-release/series-g): Company Press Release - [PyPI download stats for the official cerebras-cloud-sdk package](https://pypistats.org/api/packages/cerebras-cloud-sdk/recent): Package Registry Stats ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.