Verify True Uncensorship Policies
True uncensorship means the model does not refuse lawful adult, fictional, or controversial topics based on marketing-driven safety layers. Many providers claim to be unfiltered but still apply soft blocks for certain keywords or themes. To verify this, send prompts with explicit content and check for refusals. Our uncensored model answers without content refusals for lawful adult use. The only hard limit is sexual content involving minors, which is always refused. This ensures your application can handle diverse creative writing needs without unexpected interruptions.
Check API Compatibility Standards
Compatibility ensures you can integrate the API using standard SDKs without custom adapters. Look for an OpenAI-compatible endpoint structure, specifically POST /v1/chat/completions. This allows you to swap models easily if needed. Our API follows this standard, making it a drop-in solution for existing projects. You only need to change the base URL and API key. Avoid APIs that require custom authentication or unique request formats, as these add development time and complexity.
Evaluate Latency and Throughput
Latency affects user experience, while throughput determines how many requests you can process simultaneously. Check the requests per minute and concurrent request limits. Our API allows 300 requests per minute per key and 8 concurrent requests. This is sufficient for most small to medium applications. If you need higher throughput, consider key rotation or scaling your architecture. Monitor your usage to avoid hitting limits during peak times.
Assess Context Window Limits
The context window determines how much information the model can retain in a single conversation. A 100,000-token window allows for deep, long-form interactions. Our API supports a 100,000-token context window, with a maximum output of 16,000 tokens per request. If you do not set max_tokens, the default is 2,048 tokens. Ensure your application handles long contexts efficiently, as this impacts memory usage and response time.
Review Streaming and Tool Support
Streaming via Server-Sent Events (SSE) improves perceived performance by sending tokens as they are generated. Our API supports streaming, including token usage in the last chunk. Additionally, function calling and JSON mode are essential for building interactive applications. Support for parameters like temperature, top_p, and stop tokens allows fine-tuning of model behavior. These features ensure your chatbot can handle complex tasks and structured data outputs.
Analyze Pricing Transparency
Transparent pricing avoids hidden fees and unexpected costs. Look for token-based prepaid models rather than subscriptions. Our API charges $0.15 per 1M input tokens and $0.50 per 1M output tokens. Errors and refusals are free, and credit never expires. Top-ups are crypto-only, with bonuses for larger amounts. This model ensures you only pay for what you use, without monthly commitments.
Test Response Consistency
Consistency ensures your application behaves predictably across different prompts and times. Test the model with various inputs to check for stability. Parameters like seed and temperature can help control randomness. Our API supports these parameters, allowing you to reproduce results when needed. Regular testing helps identify any drift in model behavior or performance issues over time.
Check Data Privacy and Training
Privacy concerns arise when providers use your prompts for training. Ensure the provider does not use your data for this purpose. Our API does not use prompts for training, ensuring your data remains private. An account requires only an email, and no phone number is needed. This minimizes data collection and protects your identity. Verify the privacy policy to confirm these claims before integrating.
