Ollama vs vLLM
Short answer
Ollama: The simplest way to download and run open-weight LLMs locally behind an API. vLLM: High-throughput LLM inference server for GPUs with an OpenAI-compatible API. Both are in our Local model runtimes category.
Choose Ollama if you want: no GPU server needed and larger community (184k vs 95.1k GitHub stars).
Ollama publishes no official RAM figure, so we cannot compare hosting cost directly.
Last updated · computed from each project's official docs and live GitHub data · sources
Ollama vs vLLM side by side
| Ollama | vLLM | |
|---|---|---|
| Category | Local model runtimes | Local model runtimes |
| What it is | The simplest way to download and run open-weight LLMs locally behind an API. | High-throughput LLM inference server for GPUs with an OpenAI-compatible API. |
| License | MIT | Apache-2.0 |
| License type | Permissive | Permissive |
| License conditions | Permissive. Internal and commercial use allowed. Individual models have their own licenses. | Permissive. Internal and commercial use allowed. Models keep their own licenses. |
| Status | Active | Active |
| GitHub stars | 184k | 95.1k |
| Last commit | Oct 22, 2026 | Oct 22, 2026 |
| Latest release | v0.40.8 | v0.32.0 |
| Minimum hardware | Not published | Not published |
| Recommended hardware | Not published | Not published |
| GPU | NVIDIA GPUs need compute capability 5.0+ and driver 550+ (570+ for compute capability 5.0–6.2). CPU-only also works. | NVIDIA: compute capability 7.5 or higher (e.g. T4, RTX 20xx, A100, L4, H100, B200). |
| Est. server cost | Not estimated | GPU server (not estimated) |
| Deploy method | Docker (or install script) | pip / uv (or Docker) |
| Known gotchas | 2 listed | 1 listed |
| Details | Full Ollama guide → | Full vLLM guide → |
Key differences
- License: Ollama: MIT (Permissive). vLLM: Apache-2.0 (Permissive).
- GPU: Ollama: optional / see notes. vLLM: needed for practical use.
- Est. server cost: Ollama: not estimated (no official RAM figure). vLLM: GPU server (not estimated).
- Deploy: Ollama: Docker (or install script) · multi-container stack. vLLM: pip / uv (or Docker) · pip / uv (or Docker).
- GitHub stars: Ollama: 184k. vLLM: 95.1k.
- Latest release: Ollama: v0.40.8 (Oct 21, 2026). vLLM: v0.32.0 (Oct 18, 2026).
Same for both: Category: Local model runtimes; Official hardware: not published; Status: Active; Last commit: Oct 22, 2026.
Ollama vs vLLM: FAQ
Ollama or vLLM: which should a small business choose?
Choose Ollama if you want: no GPU server needed and larger community (184k vs 95.1k GitHub stars). Ollama publishes no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, Ollama or vLLM?
Ollama: not estimated (no official RAM figure). vLLM: GPU server (not estimated). Our estimate is the cheapest Hetzner Cloud plan that meets each project's official RAM and vCPU figure; it covers the server only.
How much hardware do Ollama and vLLM need?
Ollama: not published. vLLM: not published. vLLM needs a GPU for practical use.
What is the license difference between Ollama and vLLM?
Ollama: MIT (Permissive). Permissive. Internal and commercial use allowed. Individual models have their own licenses. vLLM: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed. Models keep their own licenses. This is a summary, not legal advice.
Is Ollama or vLLM more actively maintained?
Ollama: Active, last commit Oct 22, 2026. vLLM: Active, last commit Oct 22, 2026. GitHub data refreshed Oct 22, 2026.
Which is easier to deploy, Ollama or vLLM?
Ollama installs via Docker (or install script) (multi-container stack); vLLM via pip / uv (or Docker) (pip / uv (or Docker)). Ollama lists 2 known gotchas and vLLM lists 1; see each app page.
Related
Sources
- Ollama GitHub repository: github.com/ollama/ollama
- Ollama documentation, Ollama deploy instructions: docs.ollama.com/docker
- Ollama license: github.com/ollama/ollama/blob/main/LICENSE
- Ollama hardware requirements: docs.ollama.com/gpu
- vLLM GitHub repository: github.com/vllm-project/vllm
- vLLM documentation, vLLM hardware requirements: docs.vllm.ai/en/latest/getting_started/installation/gpu/
- vLLM license: github.com/vllm-project/vllm/blob/main/LICENSE
- vLLM deploy instructions: github.com/vllm-project/vllm#readme
- Hetzner Cloud pricing used for cost estimates (read 2026-10-22): www.hetzner.com/cloud/regular-performance
- GitHub REST API (stars, commits, releases): docs.github.com/en/rest
Every value is generated from the same verified data as the app pages. Spotted something wrong? Tell us.