QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch
Released by g4me in 2026, QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch is an chat model. QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch is an open-weights chat model.
by g4me
Best for
Ways to use QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your g4me API key. osFoundry discovers QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch
Is QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch free to use?
QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch locally?
Yes. QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch best at?
QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch is well-suited to text generation.
How do I use QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch in osFoundry?
Paste your g4me API key in the key dialog (or deploy the open weights for self-hostable models), assign QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by g4me on April 8, 2026. Source: https://huggingface.co/g4me/QWiki-Base-LR1e5-b32g2gc8-ck2048-order-batch