e9f26c47-9b78-4e3f-8144-f2727928962b
e9f26c47-9b78-4e3f-8144-f2727928962b is a 2727928962 billion parameter chat model from VERSIL91, released December 28, 2024. e9f26c47-9b78-4e3f-8144-f2727928962b is an open-weights chat model with roughly 2727928962 billion parameters.
by VERSIL91 · 2727928962B parameters
Best for
- complex multi-step reasoning
- agent orchestration with tool use
- long-document analysis and summarisation
Ways to use e9f26c47-9b78-4e3f-8144-f2727928962b in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your VERSIL91 API key. osFoundry discovers e9f26c47-9b78-4e3f-8144-f2727928962b 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
e9f26c47-9b78-4e3f-8144-f2727928962b 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 e9f26c47-9b78-4e3f-8144-f2727928962b
e9f26c47-9b78-4e3f-8144-f2727928962b runs on a multi-GPU setup or H200 141GB at Q4 (~1636757378 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~6547029509 GB).
e9f26c47-9b78-4e3f-8144-f2727928962b vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about e9f26c47-9b78-4e3f-8144-f2727928962b
Is e9f26c47-9b78-4e3f-8144-f2727928962b free to use?
e9f26c47-9b78-4e3f-8144-f2727928962b 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 e9f26c47-9b78-4e3f-8144-f2727928962b 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 e9f26c47-9b78-4e3f-8144-f2727928962b need?
Approximately 1636757378 GB at Q4 quantisation, or 6547029509 GB at full FP16 precision. Requires multi-GPU at higher quantisation.
Can I run e9f26c47-9b78-4e3f-8144-f2727928962b locally?
Yes. e9f26c47-9b78-4e3f-8144-f2727928962b is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is e9f26c47-9b78-4e3f-8144-f2727928962b best at?
e9f26c47-9b78-4e3f-8144-f2727928962b is well-suited to complex multi-step reasoning, agent orchestration with tool use, long-document analysis and summarisation.
How do I use e9f26c47-9b78-4e3f-8144-f2727928962b in osFoundry?
Paste your VERSIL91 API key in the key dialog (or deploy the open weights for self-hostable models), assign e9f26c47-9b78-4e3f-8144-f2727928962b to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by VERSIL91 on December 28, 2024. Source: https://huggingface.co/VERSIL91/e9f26c47-9b78-4e3f-8144-f2727928962b