Model selection is the new complexity in AI development. With 50+ providers and 500+ models, how do you choose the right one for each task? This guide cuts through the noise.
Choose models based on three criteria:
| Category | Best For | Examples |
|---|---|---|
| Coding | Code generation, debugging, refactoring | Claude Sonnet 4, GPT-5.4, CodeLlama |
| Reasoning | Math, logic, planning | Gemini 3.1 Pro, GPT-5.4, o1 |
| Vision | Image understanding, OCR | Gemini 3.1 Pro Vision, Claude 3.5 Sonnet |
| Writing | Content, copy, editing | GPT-5.3, Claude Opus 4.7 4, Claude Sonnet 4 |
| Chinese | Chinese language tasks | GLM 5, Kimi 2.5, DeepSeek |
| Local | Privacy, offline, zero cost | Ollama (LLaMA 3.2), LM Studio |
| Provider | Model | Cost/1M tokens |
|---|---|---|
| Anthropic | Claude Sonnet 4 | $3-5 |
| OpenAI | GPT-5.4 | $5-8 |
| Gemini 3.1 Pro | $2-4 | |
| OpenRouter | Free tier | $0 |
| Ollama | LLaMA 3.2 | $0 (local) |
# Coding task Claude Sonnet 4 — Best for full IDE integration GPT-5.4 — Good for general coding CodeLlama — Local, free # Reasoning task Gemini 3.1 Pro — 1M context, strong reasoning GPT-5.4 — General reasoning o1 — Specialized reasoning # Vision task Gemini 3.1 Pro Vision — 1M context, vision Claude 3.5 Sonnet — Vision + coding # Privacy-sensitive Ollama LLaMA 3.2 — 100% local LM Studio — Local GUI
Start with the free tier of OpenRouter or local models. Only pay when you hit limits. Match the model to the task — don't use a sledgehammer for a screw.