Fanar-2-27B-Instruct
Released by QCRI in 2026, Fanar-2-27B-Instruct is a 27 billion parameter chat model. Fanar-2-27B-Instruct is an open-weights chat model with roughly 27 billion parameters.
by QCRI · 27B parameters
Best for
Ways to use Fanar-2-27B-Instruct in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your QCRI API key. osFoundry discovers Fanar-2-27B-Instruct 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
Fanar-2-27B-Instruct 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 Fanar-2-27B-Instruct
Fanar-2-27B-Instruct runs on a 24GB consumer or workstation GPU (~17 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~65 GB).
Fanar-2-27B-Instruct vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Fanar-2-27B-Instruct
Is Fanar-2-27B-Instruct free to use?
Fanar-2-27B-Instruct 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 Fanar-2-27B-Instruct 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 Fanar-2-27B-Instruct need?
Approximately 17 GB at Q4 quantisation, or 65 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Fanar-2-27B-Instruct locally?
Yes. Fanar-2-27B-Instruct is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Fanar-2-27B-Instruct best at?
Fanar-2-27B-Instruct is well-suited to text generation.
How do I use Fanar-2-27B-Instruct in osFoundry?
Paste your QCRI API key in the key dialog (or deploy the open weights for self-hostable models), assign Fanar-2-27B-Instruct to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by QCRI on March 16, 2026. Source: https://huggingface.co/QCRI/Fanar-2-27B-Instruct