magnum-v4-123b
Built by anthracite-org, magnum-v4-123b is a 123 billion parameter chat model. magnum-v4-123b is an open-weights chat model with roughly 123 billion parameters.
by anthracite-org · 123B parameters
Best for
Ways to use magnum-v4-123b in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your anthracite-org API key. osFoundry discovers magnum-v4-123b 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
magnum-v4-123b 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 magnum-v4-123b
magnum-v4-123b runs on a single A100 80GB or H100 80GB at Q4 quantisation (~74 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~296 GB).
magnum-v4-123b vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about magnum-v4-123b
Is magnum-v4-123b free to use?
magnum-v4-123b 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 magnum-v4-123b 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 magnum-v4-123b need?
Approximately 74 GB at Q4 quantisation, or 296 GB at full FP16 precision. Fits on a single A100/H100 80GB.
Can I run magnum-v4-123b locally?
Yes. magnum-v4-123b is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is magnum-v4-123b best at?
magnum-v4-123b is well-suited to text generation.
How do I use magnum-v4-123b in osFoundry?
Paste your anthracite-org API key in the key dialog (or deploy the open weights for self-hostable models), assign magnum-v4-123b to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by anthracite-org on September 27, 2024. Source: https://huggingface.co/anthracite-org/magnum-v4-123b