What is a Large Language Model (LLM)? A Beginner's Guide
An explanation of LLM basics, mechanisms, and comparisons of major models for beginners. Learn the differences between GPT-4, Claude, and Gemini and practical application methods.
What is a Large Language Model (LLM)? A Beginner's Guide
Why Do We Need to Understand LLMs Now?
In 2025, generative AI services like ChatGPT, Claude, and Gemini are dramatically changing our work and daily lives. At the core of these services is the LLM (Large Language Model).
LLMs are not just "smart chatbots". They are versatile AI technologies that can assist with many intellectual tasks, including document creation, translation, data analysis, and programming support. Leading companies are also implementing them, with cases reporting 70% improvement in work efficiency.
In this article, we will explain everything from the basics of LLMs to practical application methods in a way that even AI beginners can understand.
What is an LLM?
Basic Definition
An LLM (Large Language Model) is an AI model that learns from vast amounts of text data and can understand and generate human language. As the word "large-scale" suggests, it consists of a massive neural network with billions to trillions of parameters (adjustable variables).
To put it simply, an LLM is like "a very knowledgeable assistant who has read tens of millions of books". However, instead of "thinking" like humans do, it generates the most appropriate responses from statistical patterns.
What LLMs Can Do
- Document creation: Blog articles, emails, drafts of business plans
- Translation: High-quality translation between multiple languages
- Summarization: Extracting key points from long documents
- Question answering: Responses based on specialized knowledge
- Code generation: Programming assistance
- Data analysis: Extracting insights from text data
How Do LLMs Work?
Understanding the Mechanism Simply
The operating principle of LLMs is complex, but it can be explained in three steps for beginners.
1. Learning Phase
It reads vast amounts of text data, including books, articles, and websites on the internet, and learns the relationships and patterns between words. For example, it statistically remembers patterns such as "today" being often followed by "the weather is good" or "I'm tired".
2. Prediction Phase
When a user inputs a question or instruction, it predicts "the optimal next word" one by one based on the learned patterns to generate sentences. This prediction is done probabilistically, creating natural responses that fit the context.
3. Adjustment Phase
It is fine-tuned based on human feedback to provide more useful and safe responses. This allows it to avoid inappropriate content and provide answers that align with user intentions.
Important Points
LLMs are statistical models learned from past data. Therefore, they have the following characteristics:
- ✅ Can access vast amounts of knowledge
- ⚠️ Don't know information after the time of learning data
- ⚠️ Sometimes generate "plausible lies" (hallucinations)
Comparison of Major LLMs: GPT-4, Claude, Gemini
In 2025, there are three major LLM providers. It's important to understand the characteristics of each and use them according to your needs.
GPT-4 / GPT-5 (OpenAI)
Features:
- Balances cutting-edge performance with human-like dialogue
- Widely adopted as ChatGPT
- GPT-5 excels in specialized thinking, GPT-4o is strong in natural conversation
Recommended Uses:
- Creative writing
- Complex problem-solving
- Situations requiring natural dialogue
Price Range: Medium to high
Claude (Anthropic)
Features:
- High safety and reliability through "Constitutional AI"
- Suitable for processing corporate confidential information
- Strong in understanding long texts and providing accurate responses
Recommended Uses:
- Corporate legal and compliance work
- Processing documents containing confidential information
- Professional work requiring accuracy
Price Range: Medium
Gemini (Google)
Features:
- Overwhelming context length of 2 million tokens
- Multimodal support (simultaneous processing of text, images, and videos)
- Integration with Google ecosystem
Recommended Uses:
- Analysis of extremely long documents
- Multimedia processing including images and videos
- When you want to keep costs down
Price Range: Low to medium
How to Choose by Use Case
| Priority | Recommended Model |
|---|---|
| Cutting-edge performance | GPT-5 |
| Reliability and safety | Claude |
| Cost performance | Gemini |
| Natural dialogue | GPT-4o |
| Extremely long text processing | Gemini 2.5 Pro |
In the future, "multi-LLM architecture", which uses different LLMs for each task, is predicted to become mainstream.
Real-World Examples: Use Cases by Leading Companies
Case 1: Mercari, Inc.
Using GPT-4, they developed "Mercari AI Assist", which automatically generates attractive product descriptions just by sellers entering the product title and simple information. This made it easy for beginners to list items.
Case 2: Internet Advertising Industry
By linking ChatGPT API with proprietary ad effectiveness prediction AI, they automatically generated large amounts of ad text predicted to be highly effective from product information and target audience data. This significantly reduced advertising creation time.
Case 3: Customer Support
By introducing LLMs as 24-hour customer support, they can respond to customer questions immediately even on holidays and late at night. Human operators can now concentrate only on complex issues.
What Beginners Can Do Right Now
1. Try Services Available for Free
- ChatGPT (OpenAI): Basic features available on free plan
- Gemini (Google): Free use with Google account
- Claude (Anthropic): Free plan available
First, try simple questions or document creation. It's recommended to start with everyday uses like "Tell me about XX" or "Summarize this text".
2. Learn How to Write Prompts (Instructions)
To get good results from LLMs, it's important to give clear and specific instructions.
Bad Example:
"Create presentation materials"
Good Example:
"Please create presentation materials for a new product for sales. The target is business professionals in their 30s, the product features are XX, and I'd like about 10 pages"
3. Integrate with Business Tools
Many business tools have integrated LLMs. For example:
- Microsoft 365 Copilot: AI assistance in Word, Excel, PowerPoint
- Notion AI: Efficient document creation
- Google Workspace: Gemini utilization in Gmail, Docs, Sheets
4. For Presentation Creation: "QuickSlide"
The AI tool QuickSlide (provided by wizPulseAI), specialized in presentation material creation, maximizes the power of LLMs to automatically generate high-quality slides in just a few minutes.
QuickSlide Features:
- Multi-language support including Japanese, English, Arabic
- Abundant templates safe for beginners
- Designs optimized for business scenarios
Summary: Understand LLMs and Gain the Future of Work
LLM (Large Language Model) is no longer a science fiction technology, but a practical tool that supports our daily work.
What We Learned in This Article:
- ✅ LLMs are language AI learned from vast amounts of data and can assist with diverse intellectual tasks
- ✅ GPT-4, Claude, and Gemini each have different strengths and should be chosen according to use case
- ✅ Leading companies are utilizing them widely in writing, customer support, marketing, and more
- ✅ Even beginners can start with free services, and with proper prompt writing, can achieve significant results
Action Plan to Start Today
- Today: Register for free with ChatGPT or Gemini and try simple questions
- This week: Actually use it in work situations (email creation, summarization, etc.)
- This month: Learn how to write prompts and become able to give effective instructions
- After 3 months: Integrate LLMs into your workflow and experience time savings
AI value changes depending on the skills of the user. Start touching it little by little from today and experience the possibilities of new ways of working.
Frequently Asked Questions (FAQ)
Q1: Can I use LLMs for free?
Many LLM services have free plans. ChatGPT, Gemini, and Claude all allow you to try basic features for free. However, advanced features and high-volume use require paid plans.
Q2: Are LLM responses always accurate?
No. LLMs sometimes generate "plausible lies" (hallucinations). Please check important information against other reliable sources.
Q3: When using in a company, is security okay?
When handling confidential information, choose an enterprise plan (contract that doesn't use data for learning) or consider on-premise LLMs. Claude is designed with a particular emphasis on security.
Q4: Can I use it without programming knowledge?
Yes. Modern LLM services are in chat format and can be used just by giving instructions as in everyday conversation. Programming knowledge is not required.
Q5: I don't know which LLM to choose
We recommend trying several with free plans first. If you do a lot of writing, GPT-4 is good, if you prioritize accuracy, Claude, and if you prioritize cost, Gemini.
Related Articles
- Complete ChatGPT Guide: From Business Use to Advanced Tips
- Introduction to Prompt Engineering: How to Get the Best Results from AI
- Latest AI Trends 2025: 5 Trends to Watch
References
- OpenAI GPT-4 Official Documentation
- Anthropic Claude Official Site
- Google Gemini Official Information
- NTT DATA Mathematical Systems "LLM Business Utilization Guide"
- Arpable "2025 Enterprise LLM Selection Guide"
About the Author
Tomoya Tanaka is an AI researcher at wizPulseAI, conducting research on applying the latest LLM technology to business. He focuses on supporting AI implementation in leading companies and strives to provide explanations that are easy for beginners to understand.
This article was published on January 12, 2025, and created based on the latest information. AI technology is rapidly evolving, so it will be updated regularly.