프로젝트에 적합한 LLM을 선택하는 방법

Key Considerations

Choosing the right large language model (LLM) is one of the most important decisions in AI development. The wrong choice can lead to poor performance, excessive costs, or vendor lock-in.

Evaluation Criteria

• Task Fit: Does the model excel at your specific task (coding, reasoning, creative writing, summarization)?
• Context Window: How much text can the model process at once?
• Latency: How fast does the model respond?
• Cost: What are the per-token costs for input and output?
• Privacy: Can you self-host, or must you use a cloud API?

Popular Options in 2026

• Claude (Anthropic): Excellent for long documents, nuanced reasoning, and coding.
• GPT-4o (OpenAI): Strong multimodal capabilities, fast inference.
• Gemini (Google): Large context windows, competitive pricing.
• Qwen (Alibaba): Best-in-class Chinese performance, open-weight options.
• Llama (Meta): Fully open-source, self-hostable, strong community.

Decision Framework

Start by defining your must-haves: latency under 2 seconds? Under $0.01 per 1K tokens? Full data sovereignty? Then benchmark 2-3 finalists on your actual data before committing.