LLM API Relay Free Credits: A Compliance and Usage Guide

1. Clarify Use Cases Before Applying

Free credits are suitable for three tasks: comparing outputs from different models on the same task, verifying that an API integration works, and estimating call costs after launch. If the goal is to support production traffic reliably over the long term, free credits usually cannot serve as the foundation. Use free credits only for lawful testing. Do not use them to generate illegal content, conduct attacks or fraud, or circumvent platform risk controls.

Before you start, write down three questions: Which models does this test need? How many calls do you expect? Roughly how many tokens will each request use? Only when all three answers are clear can you judge whether a platform’s free credit is sufficient.

Here are short answers to several common questions.

• Can free credits be used commercially? Most platforms’ free credits are limited to testing or trials. Whether they can be used for online services depends on the platform terms. Confirm the terms before launch.
• Can I register multiple accounts? Multiple accounts usually violate platform terms and trigger risk controls.
• Can I share credits with others? Credits and accounts must not be lent, resold, or shared with unrelated people.
• What if I exceed the limit and owe fees? First check the billing and charge records in the console, then contact platform support to confirm. Setting budget alerts and usage caps in advance can reduce overages.

2. Common Forms of Free Credits

Free credit offerings from API relay services generally fall into five categories. The main differences are how the credit is counted, when it expires, and where it can be used.

Form	What is provided	Common restrictions	Suitable for	Main risk
Registration balance	A fixed usable balance	Limited models, some toolchains unavailable, expiration date	Developers who want to compare multiple models quickly	Unused balance expires
Call-count credits	A fixed number of model calls	Call count is tied to model tier; advanced models may be converted into multiple calls	Users with clear test scenarios	Consumption is faster than expected after switching models
Periodic membership quota	Membership and weekly quota for a period	Quota resets weekly or expires; rules are relatively complex	Users who can use the service continuously	Credits are wasted if validity is ignored
Check-in and activity rewards	Small daily balance or tokens	Small amounts; long-term use is needed to accumulate value	Long-term light users	Reward rules change frequently
Credit points	A larger nominal virtual credit	Credit-to-cash deduction ratio may differ	Users who understand billing rules	Unclear conversion means actual usable value is lower than expected

The amount of free credit varies by platform; refer to platform announcements and billing pages. Do not look only at the nominal amount. Check which models can actually be called and whether the credit can be used in your scenario.

Cost estimate example (assumed values): If a model charges USD 2 per million tokens and a short conversation consumes about 800 tokens, the cost per call is 800 ÷ 1,000,000 × 2 = USD 0.0016. A USD 1 balance supports about 625 such calls.

This estimate covers only input and output tokens for one successful call. It does not include failed retries, cache differences, model premiums, minimum charges, exchange rates, or taxes. Actual unit prices and usage are subject to the platform’s billing page and announcements.

Credit conversion example (assumed values): If a platform lists 100 credit points and the deduction rule is 1 credit point = CNY 0.005, the actual deductible value is CNY 0.5. After receiving credit points, first find the conversion rule on the billing page, then use a small call to confirm that the deduction matches expectations.

3. Registration Risk Controls

To reduce bulk registration and abuse, most platforms apply risk controls. These rules change over time. Before registering, read the latest terms and billing rules, take screenshots or notes, and record the verification date for later comparison.

3.1 Email restrictions

Some platforms accept only specific email providers or educational domains. Disposable temporary email addresses and obscure domains have a high failure rate, and some platforms freeze such accounts. Use a common email address that you hold long term and that can receive verification messages. Do not misuse or trade educational email addresses; violating the terms may lead to account suspension.

3.2 Phone verification

Some platforms require a bound phone number before credits are enabled. If you do not have a number for the required region, first confirm whether the platform supports numbers from your region or offers another official verification method.

Do not use temporary numbers, SMS-receiving services, or third-party verification. Such numbers cannot prove the account holder’s identity, accounts are easily frozen, and later appeals or quota increases usually cannot be processed. If the platform does not accept your number, choosing another platform is safer than bypassing verification.

3.3 Third-party account login

Some platforms support login with Google or GitHub. This saves the step of filling in registration details. An existing, commonly used account makes login smoother, but this only reduces the cost of bulk registration; it is not identity verification.

If the third-party account is disabled, the platform account may also become inaccessible. Set a separate password for the platform account, enable two-factor authentication, and record recovery methods. Isolate API keys and platform permissions from your main personal account, for example by using a separate project or permission group provided by the platform.

4. Compliance Boundaries

When using free credits, keep the following boundaries.

• Do not resell, lend, or share accounts or credits.
• Do not register in bulk or use multiple accounts to obtain credits.
• Do not bypass risk controls, verification, or rate limits.
• Do not use the service for illegal content, attacks, fraud, or harassment.

Platform terms: Before launch, check the terms of service item by item for commercial use, data retention, and usage restrictions, and archive them.

Content safety: Build filtering and review mechanisms for model output, especially content shown to users. The user is responsible for output content; using a third-party API does not remove that responsibility.

Data privacy: Test data must not contain real users’ phone numbers, identity document numbers, bank card numbers, or other personal information. When needed, replace it with fictitious data or redact it before upload.

API key handling: Follow these steps:

1. Do not write keys into frontend code, mobile app packages, or public documentation.
2. Do not commit keys to code repositories. For local development, read them from environment variables or a secrets management service.
3. Create keys with least privilege. Use different keys for different purposes.
4. Rotate keys regularly. If a leak is suspected, revoke the old key in the platform console immediately.
5. In logs, keep only the last few characters of a key. Do not record the full key.

Overages and service shutdown: Set budget limits and usage alerts in the platform console. When credits are exhausted or the platform shuts down service, export call records and test results. Reserve model and platform switching configuration in your code to avoid business interruption caused by a single platform failure.

5. Selection and Acceptance from Trial to Launch

Selection checklist

Selection dimension	Question to verify	Criterion
Model coverage	Are the target models callable? Are version numbers clearly labeled?	All target models are available.
Credit validity	When do free credits expire? Do they reset weekly?	Validity covers the test period.
Model and toolchain restrictions	Which models and features are unavailable?	Core tests are not affected.
RPM/TPM concurrency	What are the per-minute request and token limits?	Higher than the concurrency required for load testing.
Billing transparency	Are unit prices, conversion rules, and charge details available?	Each charge can be recalculated from the details.
Data compliance	How long is data retained? Is it used for training? Where is it stored?	Written documentation exists and meets business requirements.
SLA and support	What are the availability commitment, incident notifications, and ticket response times?	Clear commitments and contact channels exist.

Acceptance checklist from trial to launch

• Functionality: API calls to all target models succeed, response formats meet business parsing requirements, and exception responses have corresponding handling logic.
• Performance: At the target concurrency, first-token latency and total latency meet business requirements; timeout and retry policies are configured.
• Cost: Estimate monthly costs using real request samples and set budget alerts.
• Stability: Run continuously for a period without abnormal interruptions. Rate limits and errors are recorded, and backup model or backup platform plans exist.
• Security: API keys have been removed from code and repositories, permissions are minimized, and a rotation plan is in place.
• Compliance: Platform terms have been confirmed to allow the intended use.