Ollama is the tool that made local LLMs boring — in the best way.
The entire setup: brew install ollama (or download the installer), ollama pull llama3.3, ollama serve. Three commands and you have a local endpoint compatible with OpenAI's API shape.
The model library: Qwen3, Llama 3.3, DeepSeek R1 Distill, Mistral, Phi-4, Gemma 3, gpt-oss, CodeLlama — hundreds of GGUF quantizations pre-configured. Want a 70B model? ollama pull llama3.3:70b and wait.
Integration: every local-first tool in the PeaBox stack points at Ollama by default. Our Workbench, PromptVault, and Speech Studio all treat it as the base provider. It's the missing default.
Where it falls short: high-throughput production serving. If you're running 1,000 requests a second, use vLLM or SGLang. For personal machines, laptops, and small teams, Ollama is the answer.
The quiet killer feature: it handles the GPU/CPU offloading for you. If your GPU runs out of VRAM, the rest spills to RAM/CPU transparently. It just works — most of the time.