JiRackTernary_70b
Built by kgrabko, JiRackTernary_70b is a 70 billion parameter chat model. JiRackTernary_70b is an open-weights chat model with roughly 70 billion parameters.
by kgrabko · 70B parameters
Best for
Ways to use JiRackTernary_70b in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your kgrabko API key. osFoundry discovers JiRackTernary_70b 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_70b 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_70b
JiRackTernary_70b runs on a single A100 80GB or H100 80GB at Q4 quantisation (~42 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~168 GB).
JiRackTernary_70b vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about JiRackTernary_70b
Is JiRackTernary_70b free to use?
JiRackTernary_70b 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_70b 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_70b need?
Approximately 42 GB at Q4 quantisation, or 168 GB at full FP16 precision. Fits on a single A100/H100 80GB.
Can I run JiRackTernary_70b locally?
Yes. JiRackTernary_70b is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is JiRackTernary_70b best at?
JiRackTernary_70b is well-suited to text generation.
How do I use JiRackTernary_70b in osFoundry?
Paste your kgrabko API key in the key dialog (or deploy the open weights for self-hostable models), assign JiRackTernary_70b 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 February 2, 2026. Source: https://huggingface.co/kgrabko/JiRackTernary_70b