Local vs Cloud Models
You have two main options for accessing language models: call a cloud API like OpenAI or Anthropic, or run models directly on your own hardware. Each approach has distinct tradeoffs worth understanding.
Cloud API Models
Services like GPT-4, Claude, and Gemini run on provider infrastructure. You send requests over the internet and receive responses.
Advantages:
- Best available quality — frontier models live in the cloud
- No setup or maintenance — just get an API key
- Always updated with latest improvements
- Works on any device with internet
Disadvantages:
- Costs money per request
- Your data travels to external servers
- Rate limits can throttle heavy usage
- Requires internet connectivity
Local Models
Open-source models like Llama, Mistral, and CodeLlama can run entirely on your machine.
Advantages:
- Free after initial setup
- Complete privacy — data never leaves your machine
- No internet required
- Unlimited usage without rate limits
Disadvantages:
- Lower quality than frontier cloud models
- Requires capable hardware
- Setup and maintenance overhead
- You manage updates yourself
Running Models Locally
Several tools make local models accessible:
Ollama provides the easiest path — install it, then run models with simple commands. LM Studio offers a graphical interface for browsing and chatting with models. llama.cpp gives maximum control for technical users.
Hardware Requirements
Local models need substantial resources:
7B parameter model: 8GB RAM minimum
13B parameter model: 16GB RAM minimum
70B parameter model: 64GB+ RAM or dedicated GPU
Apple Silicon Macs: Excellent for local inference
NVIDIA GPUs: Best performance for larger models
CPU-only: Works but noticeably slower
When to Use Each
Choose cloud APIs when:
- You need the best possible quality
- Usage is occasional (pay-per-request is fine)
- You want zero infrastructure management
- You need cutting-edge capabilities
Choose local models when:
- Privacy requirements prohibit external data transfer
- High volume makes API costs prohibitive
- You need offline capability
- You're learning and experimenting
Many developers use both — cloud APIs for production and complex tasks, local models for experimentation and privacy-sensitive work.