cl-macro-27b-lora
cl-macro-27b-lora is a 27 billion parameter chat model from j14i, released May 10, 2026. cl-macro-27b-lora is an open-weights chat model with roughly 27 billion parameters.
by j14i · 27B parameters
Best for
Ways to use cl-macro-27b-lora in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your j14i API key. osFoundry discovers cl-macro-27b-lora 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
cl-macro-27b-lora 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 cl-macro-27b-lora
cl-macro-27b-lora 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).
cl-macro-27b-lora vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about cl-macro-27b-lora
Is cl-macro-27b-lora free to use?
cl-macro-27b-lora 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 cl-macro-27b-lora 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 cl-macro-27b-lora need?
Approximately 17 GB at Q4 quantisation, or 65 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run cl-macro-27b-lora locally?
Yes. cl-macro-27b-lora is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is cl-macro-27b-lora best at?
cl-macro-27b-lora is well-suited to text generation.
How do I use cl-macro-27b-lora in osFoundry?
Paste your j14i API key in the key dialog (or deploy the open weights for self-hostable models), assign cl-macro-27b-lora to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by j14i on May 10, 2026. Source: https://huggingface.co/j14i/cl-macro-27b-lora