--- title: "Beam free inference" description: "$30 in credits refresh on a published schedule. See verified limits, model IDs, privacy terms, and primary sources for Beam." canonical_url: "https://freeinferencing.com/provider/beam_cloud/" md_url: "https://freeinferencing.com/provider/beam_cloud.md" last_updated: "2026-09-19" --- # Beam > $30 in credits refresh on a published schedule. ## Classification - **Directory:** Current - **Free access:** Monthly credits - **Status:** Available now - **Confidence:** High - **Payment card:** Yes - **Account:** Required - **Equivalent paid value:** $30.00/mo - **API endpoint:** `https://{app}-{deployment}-v{version}.app.beam.cloud` ## Models mentioned No stable model IDs were recorded in this snapshot. ## Limits and terms ```yaml plan_price_usd_per_month: 0 included_credit_usd_per_month: 30 reset: monthly gpu_concurrency: 5 cpu_concurrency: 30 api_requests: unlimited ``` ## What happens to your prompts? **Not private.** Beam permits storage and expressly permits use of customer data and queries to measure and improve the service. 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: Beam cloud compute, APIs, and customer-deployed models under Smartshare's public terms. prompt_retention: Beam's terms say it may hold and store Your Data on the customer's behalf, but they do not publish an inference-payload retention period or a zero-retention default. response_retention: Outputs and other customer-created data can be stored under the same customer-data provisions; no fixed deletion schedule is published. ordinary_logging: Account, browser, IP, site-use, and service metadata are collected, and customer queries, submitted models, and usage metadata may be processed to measure and improve the service. model_training: not_documented product_improvement: The terms expressly permit Beam to use customer data, queries, submitted models, and usage metadata to measure and improve the service. human_or_operator_access: Stored data may be processed to provide, monitor, support, and improve the service; the public documents do not define operator-access restrictions for inference content. subprocessors_and_routing: Beam uses infrastructure and service subprocessors including Google and Sentry and offers a DPA on request for EU personal data. deletion_controls: Personal-data correction and deletion requests are available, but no service-content deletion deadline or self-service inference-history control is documented. caveat: The public agreement provides broad improvement permission and is silent on model training and inference retention. Do not submit sensitive data without a negotiated DPA and clearer controls. agreements: terms_and_conditions: https://docs.beam.cloud/v2/security/terms-and-conditions privacy_policy: https://docs.beam.cloud/v2/security/privacy-policy ``` ## Eligibility ```yaml account_required: true payment_method_required: true plan_selection_required: Developer pay-as-you-go ``` ## API compatibility and modalities - **Compatibility:** Custom Rest, OpenAI Compatible Via Vllm Or Sglang - **Modalities:** Text generation, Custom models ## Before you build with Beam ### 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. “Monthly credits” 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 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 Beam permits storage and expressly permits use of customer data and queries to measure and improve the service. 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 - [Pricing](https://www.beam.cloud/pricing): Official Pricing - [FAQ](https://docs.beam.cloud/v2/resources/faq): Official Docs - [Endpoint overview](https://docs.beam.cloud/v2/endpoint/overview): Official Docs - [vLLM OpenAI-compatible server](https://docs.beam.cloud/v2/examples/vllm): Official Example - [Monthly credit confirmation](https://www.beam.cloud/blog/serverless-gpu-reinforcement-learning): Official Announcement - [Beam Terms and Conditions](https://docs.beam.cloud/v2/security/terms-and-conditions): Official Terms - [Beam Privacy Policy](https://docs.beam.cloud/v2/security/privacy-policy): Official Privacy - [Beam Subprocessor List](https://docs.beam.cloud/v2/security/subprocessor-list): Official Docs - [PyPI download stats for beam-client](https://pypistats.org/api/packages/beam-client/recent): Package Registry Stats - [beam-cloud/beta9 serverless GPU runtime](https://github.com/beam-cloud/beta9): Official Repository ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.