7aba420b-74ac-4209-b514-ce8bf69ca7a5
Released by duyphu in 2025, 7aba420b-74ac-4209-b514-ce8bf69ca7a5 is a 420 billion parameter chat model. 7aba420b-74ac-4209-b514-ce8bf69ca7a5 is an open-weights chat model with roughly 420 billion parameters.
by duyphu · 420B parameters
Best for
- complex multi-step reasoning
- agent orchestration with tool use
- long-document analysis and summarisation
Ways to use 7aba420b-74ac-4209-b514-ce8bf69ca7a5 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your duyphu API key. osFoundry discovers 7aba420b-74ac-4209-b514-ce8bf69ca7a5 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
7aba420b-74ac-4209-b514-ce8bf69ca7a5 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 7aba420b-74ac-4209-b514-ce8bf69ca7a5
7aba420b-74ac-4209-b514-ce8bf69ca7a5 runs on a multi-GPU setup or H200 141GB at Q4 (~252 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~1008 GB).
7aba420b-74ac-4209-b514-ce8bf69ca7a5 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about 7aba420b-74ac-4209-b514-ce8bf69ca7a5
Is 7aba420b-74ac-4209-b514-ce8bf69ca7a5 free to use?
7aba420b-74ac-4209-b514-ce8bf69ca7a5 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 7aba420b-74ac-4209-b514-ce8bf69ca7a5 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 7aba420b-74ac-4209-b514-ce8bf69ca7a5 need?
Approximately 252 GB at Q4 quantisation, or 1008 GB at full FP16 precision. Requires multi-GPU at higher quantisation.
Can I run 7aba420b-74ac-4209-b514-ce8bf69ca7a5 locally?
Yes. 7aba420b-74ac-4209-b514-ce8bf69ca7a5 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is 7aba420b-74ac-4209-b514-ce8bf69ca7a5 best at?
7aba420b-74ac-4209-b514-ce8bf69ca7a5 is well-suited to complex multi-step reasoning, agent orchestration with tool use, long-document analysis and summarisation.
How do I use 7aba420b-74ac-4209-b514-ce8bf69ca7a5 in osFoundry?
Paste your duyphu API key in the key dialog (or deploy the open weights for self-hostable models), assign 7aba420b-74ac-4209-b514-ce8bf69ca7a5 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by duyphu on January 24, 2025. Source: https://huggingface.co/duyphu/7aba420b-74ac-4209-b514-ce8bf69ca7a5