ollama vs vllm
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| ollama | vllm | |
|---|---|---|
| Tagline | Local inference runtime and CLI for open-weight large language models | A high-throughput and memory-efficient inference and serving engine for LLMs |
| Stars | 176k | 86k |
| Forks | 17k | 19k |
| Open issues | 3.4k | 5.6k |
| Language | Go | Python |
| License | MIT | Apache-2.0 |
| Last pushed | Jul 7, 2026 | Jul 7, 2026 |
| Categories | Inference & Serving, LLM Frameworks, Developer Tools | Inference & Serving |
ollama
Ollama provides a command-line interface and REST API to locally run, manage, and serve open-source LLMs with minimal setup. It abstracts dependencies like GGUF handling and GPU acceleration behind lightweight cross-platform binaries.
Go
vllm
vLLM is a fast and easy-to-use library designed for efficient Large Language Model (LLM) inference and serving. It includes state-of-the-art performance with features like PagedAttention, quantization support, optimized attention kernels, and seamless integration with Hugging Face models.
Python