AI search engines vs. LLMs – what’s behind it and what matters in 2025?

Since ChatGPT exploded, artificial intelligence is suddenly everywhere – in apps, at work, and in search. But what exactly is the difference between an LLM like GPT-4 and an AI search engine like Perplexity or Copilot? Many throw both into the same bucket – even though the goals are completely different. In this article I’ll explain clearly what’s really behind it and which tools you should know.

LLM vs. AI search – what does what?

LLMs (Large Language Models) are language models trained on massive amounts of text. They are designed to write texts, translate, generate code, or answer complex questions – in a way that feels like a human conversation. This is enabled by NLP – natural language processing.

AI search engines work differently: they summarize information from real sources. Instead of throwing ten links at you, tools like Perplexity or Copilot deliver a clear answer right away – including sources. This is made possible by RAG models (retrieval-augmented generation), which pull in external content instead of “making things up” like classic LLMs can (also known as hallucination).

Top LLMs at a glance

• GPT-4o (OpenAI): Multimodal model with text, image & audio. Fast, smart, and available in a “mini” version for mobile.
• Mistral / Mixtral: European open-source model, especially strong for coding & support topics.
• Llama 3 (Meta): Transparent, efficient, open source. Strong performance, especially the 70B variant.
• Gemini & Gemma 2 (Google): Multimodal, huge context window – ideal for visual and complex tasks.
• Claude 3.5 (Anthropic): Focus on ethics & accuracy. Delivers top answers, even for long texts.
• SEA-LION, ERNIE & Grok: Regional models, e.g. for Asia. Linguistically and culturally adapted.

The most exciting AI search engines in 2025

• Perplexity AI: Super fast, clean interface, and cites sources well. Uses RAG architecture and multiple LLMs.
• Google SGE: Google experiment with AI summaries directly above classic results.
• Microsoft Copilot: GPT-4 inside Bing. Seamless integration into Office 365 – great for research & productive work.
• Andi Search: Clean design, chatbot feel. Especially good for understanding topics and going deeper.
• Phind: Developer tool focused on coding & technical questions – delivers code and explains it immediately.
• Waldo: For academic research, with citations and sources – very structured, more niche.
• Brave Search: Search without trackers & ads. Has its own index and generates AI overviews.
• Komo: Focus on privacy, delivers AI answers with a personal note. No tracking, no ads.
• You.com: Conversational search with generator, writing support, and image features – flexible & creative.
• ChatGPT (with web access): Technically an LLM – but with a browsing feature it becomes a kind of AI search engine.

Conclusion: use AI – but use it right

If you want to create content, you need an LLM. If you want to find information, an AI search engine like Perplexity is often the better choice. Tools like Copilot combine both worlds and help you get to better results faster – for SEO, content, research, or simply to keep a clear overview.

The key is knowing which tool was built for which job. Only then can you use AI in a meaningful way – and avoid relying on answers that only sound correct but are factually off.