QVAC vs WebLLM
QVAC
Open-source ecosystem for local-first peer-to-peer AI on every platform.
WebLLM
In-browser language model inference on WebGPU, with no install and no server.
Key differences
WebLLM runs language models inside a browser tab on WebGPU, with no installation and no server process. QVAC runs outside the browser, in Node.js, Bare or Expo, as a library linked into an application.
The browser sets the operating limits: a page works within the memory WebGPU grants it, model weights cache per origin and download again on a different one, and the project's scope is language models. QVAC reads and writes device storage directly, and covers speech recognition, speech synthesis, OCR, translation and image generation alongside text. The ceiling is the sandbox, not the hardware.
WebLLM and MLC LLM come from the same team and share the MLC compiler stack, so those two comparisons overlap. WebLLM targets pages loaded in a browser. QVAC targets applications installed on desktop and mobile.
This page compares WebLLM v0.2.84, released 24 April 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
WebLLM
PLATFORMS
macOS
YesYesWindows
YesYesLinux
YesYesAndroid
YesIn browser
iOS
YesIn browser
AI TASKS
Text generation
YesYesTranscription
YesTranslation
YesImage generation
YesOCR
YesText-to-speech
YesRUNTIME SUPPORT
Node.js
YesBrowser only
Bare
YesExpo
YesHTTP server
YesCLI
YesP2P
Peer discovery
YesInference delegation
YesEncrypted transport
YesMOBILE SUPPORT
On-device inference
YesIn browser
LoRA fine-tuning on mobile
YesMobile SDK
YesLICENSING
License
Apache 2.0
Apache 2.0
Open weights tooling
YesYesWhen to choose QVAC
You are shipping an installed application rather than a page.
You need more memory than a browser tab is granted.
You need speech, OCR, translation or image generation.
You want a model cached once per device rather than per origin.
When to choose WebLLM
You want zero install and a link you can share.
Your product is already a web application.
A small model in a tab covers the job.
You want to stay outside app store review.
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