LLM Models: 2026 Guide

Two types of models, two purposes

When developing with AI, you use models in two very different contexts:

⚠️ Common mistake: Using the same model for both. An expensive model that writes excellent code may be unnecessary (and costly) for answering simple user questions.

Models for coding agents (January 2026)

These models power the tools YOU use to program:

💡 SWE-bench measures how well a model solves real GitHub bugs. Higher % = better for code.

Models for production (January 2026)

These models go inside your app to serve users:

Why does context (context window) matter?

The context is how much information the model can "see" in a single conversation.

┌─────────────────────────────────────────────────────┐
│  Context = Prompt + History + Files + Output        │
└─────────────────────────────────────────────────────┘

Model with 8K context:   [████____] Only 8,000 tokens
Model with 128K context: [████████████████████████████████] 128,000 tokens
Model with 1M context:   [███████████████████████████████████████...] 1,000,000 tokens

Open Source Models: The free alternative

You don't need to pay for APIs. You can run models locally or use services like OpenRouter.

Option 1: Run locally with Ollama

# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# Download and run GLM-4
ollama run glm4

# Or DeepSeek
ollama run deepseek-v3

Requirements: GPU with 8GB+ VRAM for small models, 24GB+ for large ones.

Option 2: OpenRouter (unified API)

OpenRouter gives you access to all models with a single API Key:

// Use any model with OpenRouter
const response = await fetch('https://openrouter.ai/api/v1/chat/completions', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_OPENROUTER_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    model: 'deepseek/deepseek-chat-v3',  // Or any other
    messages: [{ role: 'user', content: 'Hello!' }],
  }),
});

Popular models on OpenRouter (January 2026):

Comparison: Which model for what?

Real workflow

1. DEVELOPING (your computer)
   └── You use Claude Code or Cursor
       └── Model: Claude Opus 4.5 / Sonnet 4
       └── Cost: ~$0.50-2 per work session

2. IN PRODUCTION (your app)
   └── Your chatbot responds to users
       └── Model: Gemini Flash or DeepSeek
       └── Cost: ~$0.01-0.10 per 1000 users/day

💡 The key: Use premium models to CREATE code, economical models to SERVE users.

Common mistakes

Practice

→ Chatbot with Gemini — Use Gemini Flash for free → API with Node — Backend for your model

Useful links

• 📖 OpenRouter - Available Models
• 📖 Ollama - Models Library
• 📖 Artificial Analysis - LLM Benchmarks
• 📖 SWE-bench Leaderboard
• 📖 Anthropic Pricing
• 📖 Google AI Pricing