QVAC vs Ollama
QVAC
Open-source ecosystem for local-first peer-to-peer AI on every platform.
Ollama
A local model runner with a CLI and an OpenAI-compatible HTTP API.
Key differences
Ollama runs language models through a background service, reached from a command line or an OpenAI-compatible HTTP endpoint on port 11434, with models pulled from its own registry. QVAC is a library compiled into an application, exposing text generation together with transcription, translation, OCR, speech synthesis, embeddings and image generation through one interface in JavaScript, TypeScript or Python.
Platform coverage differs. Ollama publishes builds for macOS, Windows, Linux and Docker. QVAC covers those and adds iOS and Android, where its fine-tuning call runs on the phone's own GPU.
The two also place the model differently relative to the application. Ollama keeps a service running on the machine and applications reach it over HTTP, so that service has to be installed and started wherever the application runs. QVAC loads the model inside the host process, so a packaged application carries its own inference with no external service to install.
This page compares Ollama v0.33.3, released 2 September 2026, against QVAC 0.18.2, meaning the SDK together with the Fabric inference engine at v10297.1.1. Every row was checked against the project's own documentation and release notes on 4 September 2026. Both projects move quickly, so check the current release before you make a decision on either one.
Feature matrix
Feature
QVAC
Ollama
PLATFORMS
macOS
YesYesWindows
YesYesLinux
YesYesAndroid
YesiOS
YesAI TASKS
Text generation
YesYesTranscription
YesAudio LLMs
Translation
YesImage generation
YesOCR
YesText-to-speech
YesRUNTIME SUPPORT
Node.js
YesYesBare
YesExpo
YesHTTP server
YesYesCLI
YesYesP2P
Peer discovery
YesInference delegation
YesEncrypted transport
YesMOBILE SUPPORT
On-device inference
YesLoRA fine-tuning on mobile
YesMobile SDK
YesLICENSING
License
MIT
MIT
Open weights tooling
YesYesWhen to choose QVAC
You are shipping an application to other people.
You target iOS or Android.
You need speech, OCR, translation or image generation.
You want inference inside your process, with no service to install.
When to choose Ollama
You want a local model answering within a few minutes.
Your stack already speaks the OpenAI HTTP API.
You work on desktop and server only.
You want a large body of third-party tutorials and integrations.
Compare
Ready to build with QVAC?
One SDK, every platform, no rent. Grab it and ship your own local-first AI.
npm install @qvac/sdk