Free LLM APIs: How to Choose a Text Generation API
Large language model APIs are useful for chatbots, summarization, coding tools, classification, extraction, and automation. Choosing an API should start with the workload rather than the model name.
Start with the task
A customer-support bot, coding assistant, document extractor, and creative writing tool have different requirements. Define the input length, expected output, structured-data needs, latency target, and error tolerance before comparing models.
Look beyond the model name
A model can be impressive in benchmarks but still be inconvenient if the API is unstable, poorly documented, or difficult to authenticate. Check the actual request format, response schema, timeout behavior, and rate limits.
Structured output matters
Applications often need JSON rather than free-form prose. When an API supports predictable JSON responses, validation becomes easier and downstream code becomes more reliable.
Build for provider changes
Wrap API calls behind a small internal interface. Store provider-specific details in one adapter so that changing models does not require rewriting the whole application.
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