--- title: "Nebius Token Factory free inference" description: "$1 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for Nebius Token Factory." canonical_url: "https://freeinferencing.com/provider/nebius_token_factory/" md_url: "https://freeinferencing.com/provider/nebius_token_factory.md" last_updated: "2026-09-19" --- # Nebius Token Factory > $1 for new accounts; it does not recur. ## Classification - **Directory:** Current - **Free access:** One-time trial - **Status:** Current trial - **Confidence:** High - **Payment card:** Unknown - **Account:** Not documented - **Equivalent paid value:** $1.00 once - **API endpoint:** `https://api.tokenfactory.nebius.com/v1` ## Models mentioned No stable model IDs were recorded in this snapshot. ## Limits and terms ```yaml signup_credit_usd: 1 expires_after_days: 30 recurrence: false ``` ## What happens to your prompts? **Partially private.** Training is excluded, but prompts and outputs may be stored by default unless zero-data-retention mode is enabled. 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: Nebius Token Factory inference and fine-tuning; speculative decoding is enabled by default unless Zero Data Retention is selected. prompt_retention: By default API prompts and outputs may be stored for speculative decoding, with no public maximum period stated in the quick guide. Enabling ZDR prevents post-request storage. response_retention: Same default speculative-decoding storage and optional ZDR as prompts. ordinary_logging: Account, billing, usage, security, and service metadata is processed under the integrated terms and DPA; ZDR applies to content rather than eliminating all metadata. model_training: Nebius states customer data is never used to train AI models. Fine-tuning data is used only for the customer's requested training. product_improvement: Stored default content is used for speculative decoding to improve inference speed, not model training; ZDR opts out of that use. human_or_operator_access: Content is processed within Nebius infrastructure and may be stored under the default; the public guide does not promise zero operator access. subprocessors_and_routing: Model hosting can occur in EU, Israel, or US locations shown per endpoint. Fine-tuning artifacts are stored centrally in the EU, and US processing relies on transfer mechanisms such as SCCs. deletion_controls: Users can enable ZDR in account settings to prevent storage after processing. Fine-tuning datasets, artifacts, and models follow separate customer resource controls. caveat: ZDR is opt-in and may reduce service level. Without it, input and output storage for speculative decoding has no stated maximum retention in the reviewed public guide. agreements: terms_of_service: https://tokenfactory.nebius.com/terms data_processing_agreement: https://tokenfactory.nebius.com/terms ``` ## Eligibility No structured eligibility block was recorded. ## API compatibility and modalities - **Compatibility:** OpenAI Compatible - **Modalities:** Model inference ## Before you build with Nebius Token Factory ### 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, Unknown 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 Unknown, and account access is not documented. 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 Training is excluded, but prompts and outputs may be stored by default unless zero-data-retention mode is enabled. 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 - [Token Factory prices](https://nebius.com/token-factory/prices): Official Pricing - [Token Factory trial and expiry](https://nebius.com/services/token-factory): Official Product - [Nebius Token Factory Terms and integrated DPA](https://tokenfactory.nebius.com/terms): Official Terms - [Nebius Token Factory Legal Quick Guide](https://docs.tokenfactory.nebius.com/legal/legal-quick-guide): Official Docs - [PyPI download stats for nebius (official whole-cloud SDK including the ai service group)](https://pypistats.org/packages/nebius): Package Registry Stats - [Nebius Python SDK](https://github.com/nebius/pysdk): Official Repository - [Nebius launches Nebius Token Factory to deliver production AI inference at scale (2025-11-05)](https://nebius.com/newsroom/nebius-launches-nebius-token-factory-to-deliver-production-ai-inference-at-scale): Company Press Release ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.