JiRackTernary_1b
JiRackTernary_1b (kgrabko, 2026) is a 1 billion parameter chat model. JiRackTernary_1b is an open-weights chat model with roughly 1 billion parameters.
by kgrabko · 1B parameters
Best for
Ways to use JiRackTernary_1b in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your kgrabko API key. osFoundry discovers JiRackTernary_1b 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
JiRackTernary_1b 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.
What hardware can run JiRackTernary_1b
JiRackTernary_1b runs on a single 16GB consumer GPU (~1 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~3 GB).
JiRackTernary_1b vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about JiRackTernary_1b
Is JiRackTernary_1b free to use?
JiRackTernary_1b 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 JiRackTernary_1b commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does JiRackTernary_1b need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run JiRackTernary_1b locally?
Yes. JiRackTernary_1b is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is JiRackTernary_1b best at?
JiRackTernary_1b is well-suited to text generation.
How do I use JiRackTernary_1b in osFoundry?
Paste your kgrabko API key in the key dialog (or deploy the open weights for self-hostable models), assign JiRackTernary_1b to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by kgrabko on January 26, 2026. Source: https://huggingface.co/kgrabko/JiRackTernary_1b