Ollama is the simplest path to local LLMs. vLLM is optimized for production serving.
Ollama¶
- Simple installation (curl + ollama run)
- Model management (pull, list, rm)
- REST API compatible with OpenAI
- Ideal for development and experimentation
- macOS, Linux, Windows
ollama pull llama3.2 ollama run llama3.2 ‘Explain Docker’ curl http://localhost:11434/api/generate -d ‘{“model”:”llama3.2”,”prompt”:”Hello”}’
vLLM¶
- PagedAttention — efficient GPU memory management
- Continuous batching — high throughput
- OpenAI-compatible API server
- Tensor parallelism (multi-GPU)
- Optimized for production
pip install vllm python -m vllm.entrypoints.openai.api_server \ –model meta-llama/Llama-3-8B-Instruct
Comparison¶
- Simplicity: Ollama >> vLLM
- Throughput: vLLM >> Ollama (2-5×)
- GPU utilization: vLLM better
- Model format: Ollama = GGUF, vLLM = HuggingFace
- CPU inference: Ollama OK, vLLM GPU-only
Ollama for Dev, vLLM for Production¶
Ollama for local development and experimentation. vLLM for production serving with high throughput.
ollamavllmllmaiinference