Guides

In-depth guides to understand the key concepts of AI

6 articles

Fine-Tuning vs RAG: When to Use Each Approach to Customize an LLM

Fine-tuning and RAG are the two main strategies for adapting an LLM to your data. They are not interchangeable: each solves a different problem. Here is the real difference.

Bitexoft · 10 min

Read

Guide

What Is a Context Window and Why It Matters When Using LLMs in Production

The context window is one of the most important concepts when working with LLMs and one of the most misunderstood. What it is, how it affects your applications, and how to manage it well.

Bitexoft · 9 min

Read

Guide

Cursor vs GitHub Copilot vs Codeium: Real-World Comparison After 30 Days

Three AI coding tools, one month of real use on production projects. What each one does well, where it disappoints, and which one makes sense for your situation.

Bitexoft · 10 min

Read

Guide

How to Choose the Right AI Model for Your Project (Decision Framework)

Choosing an AI model without clear criteria wastes time and money. This framework covers the variables that actually matter: cost, latency, privacy, quality, and maintainability.

Bitexoft · 8 min

Read

Guide

Best Open Source AI Models in 2025: Llama, Mistral, and Qwen Compared

Llama, Mistral, and Qwen lead the open source AI space in 2025. A practical comparison: real performance, how to run them locally, and when they make sense over paid models.

Bitexoft · 10 min

Read

Guide

GPT-4o vs Claude 3.5 Sonnet vs Gemini 1.5 Pro: Which One Should You Use?

A practical comparison of the three most widely used LLMs in 2025. No marketing benchmarks: what each model does well, where it falls short, and how to choose for your use case.

Bitexoft · 9 min

Read