What is the main difference between Ollama and vLLM?

Ollama and vLLM are both local model runners but differ in their approach, features, and target audience. Compare their GitHub stats, technology stack, and community adoption to make the best choice.

Which is better: Ollama or vLLM?

The choice between Ollama and vLLM depends on your specific needs, technical requirements, and team preferences. Both are quality open source solutions with active communities.

Can I migrate from Ollama to vLLM?

Migration between Ollama and vLLM is possible but requires careful planning. Consider data export/import capabilities, feature parity, and potential workflow changes.

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Ollama vs vLLM

Learn how Ollama and vLLM differ in their key features, development activity, technology stack and community adoption, so you can decide which of these local model runners is best for you.

Ollama

Runs open-source language models locally with a simple setup, plus optional cloud access for larger models when local hardware isn't enough.

Visit Ollama Read more

183,161stars+2,225(+1.2%)

Last 30 days

Last commit
4 hours ago
Repository age
3 years
Version
v0.40.4
License
MIT
Self-hosted
Yes
Repository
ollama/ollama

vLLM

Inference and serving engine for large language models, built for speed and hardware efficiency with an OpenAI-compatible API and support for a wide range of open models.

Visit vLLM Read more

93,793stars+1,158(+1.3%)

Last 30 days

Last commit
3 hours ago
Repository age
4 years
Version
v0.31.0
License
Apache-2.0
Self-hosted
Yes
Repository
vllm-project/vllm

Sponsor vLLM ongithub.com

Detailed Comparison

Ollama appears to have several advantages over vLLM, particularly in popularity and licensing. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.

Ollama wins

Community & Popularity

Ollama leads in popularity with 183,161 stars vs 93,793 stars for vLLM. The 95% higher star count indicates stronger community adoption. In terms of developer contributions, vLLM has 23,380 forks, indicating strong developer engagement.

Comparable

Growth Momentum

Ollama and vLLM are moving at much the same rate, adding 2,225 stars and adding 1,158 stars respectively over the last 30 days (+1.2% vs +1.3%). Neither is pulling away from the other on momentum alone.

Comparable

Development Activity

Both projects show recent activity, with Ollama last updated 4 hours ago and vLLM 3 hours ago.

Comparable

Technology Stack

Both tools share common technology foundations, being built with JavaScript, CSS, Bash, C, Objective-C, C++. However, they differ in their additional technology choices: Ollama uses Typescript, JSX, Golang, MATLAB while vLLM leverages Python, Rust.

Comparable

Project Maturity

Both projects started around the same time, with Ollama beginning 3 years ago and vLLM 4 years ago.

Ollama wins

Licensing

Ollama uses the MIT license, which is more permissive than vLLM's Apache-2.0 license, potentially offering greater flexibility for commercial use and integration.

Comparable