The Unrestricted AI Production Checklist
Before you put an unrestricted AI model into production, check nine things: compatibility, context and output limits, token arithmetic, payment options, content tolerance, rate limits, data policy, key management and error handling. This checklist works for any provider you are evaluating.
Summary
- Verify OpenAI compatibility with one test request before writing product code.
- Calculate cost from the usage field: $0.15 per 1M input tokens and $0.50 per 1M output tokens.
- Test content tolerance on your own prompts, and set your product rules in your own code.
- Plan error handling early: retry only 429 and 5xx responses, and never retry a 400 or a 401.
1. Verify OpenAI Compatibility First
Point the official OpenAI SDK at https://unrestrictedllmonline.com/v1, send one short message with the model id uncensored and read the answer from choices[0].message.content.
- Check that streaming returns server-sent events.
- Check that errors come back as JSON with a status code you can branch on.
2. Check Context Window and Output Limits
The context window is 100,000 tokens. The default output length is 2,048 tokens, and the maximum per request is 16,000 tokens. Set max_tokens to the length your product needs, so that long answers do not run into the limit by accident.
Test a conversation close to the context limit and confirm that the request fails with a clear message rather than a silent cut-off.
3. Analyze Token Pricing Arithmetic
Multiply input tokens by $0.15 per 1M and output tokens by $0.50 per 1M. Compare the result with the change in your balance over a day of test traffic. Both numbers should agree within a small margin.
| Example call | Input tokens | Output tokens | Cost |
|---|---|---|---|
| Short question | 500 | 200 | $0.0002 |
| Long analysis | 50,000 | 3,000 | $0.0090 |
4. Confirm Payment Flexibility
Top-ups are paid in USDT on TRC20 or USDC on Base, starting at $20. Bonus credit applies from $50, and the credit never expires. A balance cannot go below zero, so a loop bug stops at the amount you loaded.
Decide in advance how your team will top up and who receives the usage alerts.
5. Test NSFW Tolerance Rigorously
Run a fixed set of lawful adult, fictional and controversial prompts through the endpoint. Record each refusal and each change of tone, then compare the results with your product rules.
Our model answers those requests directly. The only hard limit is sexual content involving minors, and your own product should add any further limits its users or the law require.
6. Evaluate Rate Limits and Concurrency
Each key allows 300 requests per minute and 8 requests at the same time. Compare those numbers with your peak load rather than the average, and test a burst slightly above the limit to confirm that the response is a clear 429.
7. Assess Privacy and Training Policies
Prompts are not used for training on this service. Still, confirm the terms for your use case and decide what personal data your product will send. Store only what you need and remove personal details before logging.
8. Review Account and Key Management
Keep the key in an environment variable and never in client code. Rotate it at any time from the account page; the old key stops working at once. Create one key per environment, so that a leak in testing does not affect production.
9. Define Your Error Handling Strategy
Retry only the 429 and 5xx responses, with exponential backoff and a cap on total time. Never retry a 400 or a 401, because the same request fails again. A 402 means the balance is used up, so show the user a clear message and alert the team.
Log the status code and the request id for every failure, so that each problem can be traced quickly.
Common questions
Is an unrestricted model suitable for production?
Yes, when the product rules are set in your own code and the content is tested on your own prompts. The model answers lawful adult and fictional requests directly.
Which model id should I use?
Use uncensored. It is the only model on the service, so the id does not change.
What does a typical request cost?
A short question of about 500 input tokens and 200 output tokens costs about $0.0002 at $0.15 and $0.50 per 1M tokens.
How do I start?
Sign up with Google or with an email and a password. The account starts with $0.50 of trial credit, valid for 7 days, and no card is needed.
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