LLaDA-8B-Base-cab-rl18-tulu3
Released by jacopo-minniti in 2026, LLaDA-8B-Base-cab-rl18-tulu3 is a 8 billion parameter chat model. LLaDA-8B-Base-cab-rl18-tulu3 is an open-weights chat model with roughly 8 billion parameters.
by jacopo-minniti · 8B parameters
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use LLaDA-8B-Base-cab-rl18-tulu3 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your jacopo-minniti API key. osFoundry discovers LLaDA-8B-Base-cab-rl18-tulu3 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
LLaDA-8B-Base-cab-rl18-tulu3 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 LLaDA-8B-Base-cab-rl18-tulu3
LLaDA-8B-Base-cab-rl18-tulu3 runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~20 GB).
LLaDA-8B-Base-cab-rl18-tulu3 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about LLaDA-8B-Base-cab-rl18-tulu3
Is LLaDA-8B-Base-cab-rl18-tulu3 free to use?
LLaDA-8B-Base-cab-rl18-tulu3 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 LLaDA-8B-Base-cab-rl18-tulu3 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 LLaDA-8B-Base-cab-rl18-tulu3 need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run LLaDA-8B-Base-cab-rl18-tulu3 locally?
Yes. LLaDA-8B-Base-cab-rl18-tulu3 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is LLaDA-8B-Base-cab-rl18-tulu3 best at?
LLaDA-8B-Base-cab-rl18-tulu3 is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use LLaDA-8B-Base-cab-rl18-tulu3 in osFoundry?
Paste your jacopo-minniti API key in the key dialog (or deploy the open weights for self-hostable models), assign LLaDA-8B-Base-cab-rl18-tulu3 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by jacopo-minniti on May 4, 2026. Source: https://huggingface.co/jacopo-minniti/LLaDA-8B-Base-cab-rl18-tulu3