Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777
Released by j05hr3d in 2026, Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 is a 3 billion parameter chat model. Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 is an open-weights chat model with roughly 3 billion parameters.
by j05hr3d · 3B parameters
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your j05hr3d API key. osFoundry discovers Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 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
Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 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 Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777
Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 runs on a single 16GB consumer GPU (~2 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~8 GB).
Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777
Is Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 free to use?
Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 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 Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 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 Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 need?
Approximately 2 GB at Q4 quantisation, or 8 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 locally?
Yes. Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 best at?
Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 in osFoundry?
Paste your j05hr3d API key in the key dialog (or deploy the open weights for self-hostable models), assign Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by j05hr3d on April 20, 2026. Source: https://huggingface.co/j05hr3d/Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM-seed777