--- title: "Upstage free inference" description: "$10 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for Upstage." canonical_url: "https://freeinferencing.com/provider/upstage/" md_url: "https://freeinferencing.com/provider/upstage.md" last_updated: "2026-09-19" --- # Upstage > $10 for new accounts; it does not recur. ## Classification - **Directory:** Current - **Free access:** One-time trial - **Status:** Trial + access program - **Confidence:** High - **Payment card:** Unknown - **Account:** Not documented - **Equivalent paid value:** At least $10.00 once - **API endpoint:** `https://api.upstage.ai/v1` ## Models mentioned No stable model IDs were recorded in this snapshot. ## Limits and terms No structured limits block was recorded. ## What happens to your prompts? **Not private.** Current free-service terms expressly allow storage, service improvement, AI research, and model training with inputs and outputs. 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: Upstage free API tier under the May 2026 terms and August 2026 privacy policy; paid, promotional, async, console, and third-party models differ. prompt_retention: Free-service request and response data may be stored through the end of service provision or another separately notified period for delivery, improvement, and AI research. The general paid API rule is no storage except operationally necessary state. response_retention: Same free-tier policy; asynchronous results are stored for 30 days, while request data remains until completion. ordinary_logging: Service usage records, access logs, and IP addresses are retained for three months; account, transaction, and support records have longer statutory periods. model_training: Current terms expressly allow free-service input and output data to be used for AI research and development, including training. Paid API data is not trained on without separate consent. product_improvement: Free-tier input and output data may be used for service quality improvement and R&D. Paid API content requires separate consent for logging or improvement. human_or_operator_access: Stored free-tier data can be accessed for service delivery, improvement, research, safety, and legal compliance under Upstage and subprocessor controls. subprocessors_and_routing: Some services use third-party AI providers whose policies govern content. Current privacy disclosures list Azure, OpenAI, Fireworks, and other overseas subprocessors with feature-specific retention. deletion_controls: Free data is destroyed when its stated retention or service-provision period ends; membership withdrawal deletes many account resources, subject to legal records. No free-tier immediate content-deletion control is documented. caveat: Older Upstage API terms said API data was not stored or trained on, but the current May 2026 terms create an explicit free-service exception. Do not apply the older no-training summary to today's free tier. agreements: terms_of_service: https://www.upstage.ai/terms-of-service/update-may-06-2026 privacy_policy: https://www.upstage.ai/privacy-policy/updated-aug-26-2026 ``` ## Eligibility No structured eligibility block was recorded. ## API compatibility and modalities - **Compatibility:** OpenAI Compatible - **Modalities:** Model inference - **Geography:** South Korea And Supported Regions ## Before you build with Upstage ### 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 **Not private** because Current free-service terms expressly allow storage, service improvement, AI research, and model training with inputs and outputs. 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 - [Console and API guide](https://www.upstage.ai/blog/en/guide-1-upstage-console-api): Official Guide - [API pricing](https://www.upstage.ai/pricing/api): Official Pricing - [AI Initiative 2026](https://www.upstage.ai/events/ai-initiative-2026-en): Official Program - [Upstage Terms of Use](https://www.upstage.ai/terms-of-service/update-may-06-2026): Official Terms - [Upstage Privacy Policy](https://www.upstage.ai/privacy-policy/updated-aug-26-2026): Official Privacy - [Upstage organization on Hugging Face (Solar first-party model family)](https://huggingface.co/upstage): Official Repository - [Upstage releases Solar Pro on AWS (Amazon Bedrock Marketplace, SageMaker JumpStart, AWS Marketplace)](https://www.upstage.ai/news/solar-pro-aws): Official Press Release - [PyPI download stats for langchain-upstage](https://pypistats.org/packages/langchain-upstage): Package Registry Stats ## Sitemap See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.