Runtime comparison
Ollama vs vLLM
Ollama is a MIT-licensed runtime for Linux · macOS · Windows running on CUDA · Metal · CPU · ROCm; vLLM is Apache-2.0-licensed for Linux on CUDA · ROCm. Ollama rates easier to set up (5/5 vs 2/5 in our sourced ratings). Pick Ollama for getting a model running fastest; pick vLLM for serving many requests at once.
| Spec | Ollama | vLLM |
|---|---|---|
| License | MIT | Apache-2.0 |
| Operating systems | Linux · macOS · Windows | Linux |
| GPU backends | CUDA · Metal · CPU · ROCm | CUDA · ROCm |
| Install | binary | pip / source |
| Ease of use | 5/5 | 2/5 |
| Quant formats | gguf | awq, gptq |
| Engine | llama.cpp | vllm |
| GitHub stars | 175,773 | 85,770 |
| Latest version | v0.31.2 | v0.24.0 |
| Graphical app (GUI) | No | No |
| Server mode | Yes | Yes |
| OpenAI-compatible API | Yes | Yes |
| CPU offload | Yes | No |
| Multi-GPU | Yes | Yes |
| Speculative decoding | Yes | Yes |
| LoRA support | Yes | Yes |
| KV-cache quantization | Yes | Yes |
Which should you use?
Ollama
Best for getting a model running fastest. Command line and server, installs in one line, runs on CUDA · Metal · CPU · ROCm.
Full Ollama guide →vLLM
Best for serving many requests at once. Command line and server, runs on CUDA · ROCm.
Full vLLM guide →Neither runtime changes whether a model fits — that is your memory and quantization. Check your hardware first, then pick the runtime.
Sources: Ollama github.com/ollama/ollama (as of 2026-07-11); vLLM github.com/vllm-project/vllm (as of 2026-07-08).