Do I need an LLM API if I only want text summarization?

Not necessarily.

If your only goal is text summarization, you may not need an LLM API at all. It depends on what kind of summarization you want:

You might not need an LLM API if:

• The summaries are short, simple, and rule-based
• You’re okay with extractive summarization
  • e.g. selecting the most important sentences from the original text
• You have domain-specific texts where a traditional NLP model or heuristic works well
• You want something cheap, fast, and easy to run locally

You might want an LLM API if:

• You need abstractive summaries
  • i.e. generating a new, natural-language summary rather than just copying sentences
• The input text is messy, long, or varied
• You want summaries that are more human-like, concise, and flexible
• You need the model to follow custom instructions
  • e.g. “summarize in bullet points,” “focus on action items,” “keep it under 100 words,” etc.

Alternatives to an LLM API:

• Classic NLP summarizers like TextRank or TF-IDF-based methods
• Open-source transformer models you can run locally, like BART or T5
• Domain-specific summarization tools if your content is specialized

Rule of thumb:

• If you want basic summarization, start without an LLM API.
• If you want high-quality, flexible, instruction-following summaries, an LLM API is usually worth it.

If you want, I can also help you choose between:

1. LLM API
2. local open-source model
3. traditional summarization algorithm

based on your use case.