Mythos-Llama3.2_3B
Released by 4cast in 2026, Mythos-Llama3.2_3B is a 3 billion parameter chat model. Mythos-Llama3.2_3B is an open-weights chat model with roughly 3 billion parameters.
by 4cast · 3B parameters
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use Mythos-Llama3.2_3B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your 4cast API key. osFoundry discovers Mythos-Llama3.2_3B 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
Mythos-Llama3.2_3B 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 Mythos-Llama3.2_3B
Mythos-Llama3.2_3B 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).
Mythos-Llama3.2_3B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Mythos-Llama3.2_3B
Is Mythos-Llama3.2_3B free to use?
Mythos-Llama3.2_3B 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 Mythos-Llama3.2_3B 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 Mythos-Llama3.2_3B need?
Approximately 2 GB at Q4 quantisation, or 8 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Mythos-Llama3.2_3B locally?
Yes. Mythos-Llama3.2_3B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Mythos-Llama3.2_3B best at?
Mythos-Llama3.2_3B is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use Mythos-Llama3.2_3B in osFoundry?
Paste your 4cast API key in the key dialog (or deploy the open weights for self-hostable models), assign Mythos-Llama3.2_3B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by 4cast on May 10, 2026. Source: https://huggingface.co/4cast/Mythos-Llama3.2_3B