Llama-3_3-Nemotron-Super-49B-v1_5
Built by nvidia, Llama-3_3-Nemotron-Super-49B-v1_5 is a 49 billion parameter chat model. Llama-3_3-Nemotron-Super-49B-v1_5 is an open-weights chat model with roughly 49 billion parameters.
by nvidia · 49B parameters
Best for
Ways to use Llama-3_3-Nemotron-Super-49B-v1_5 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your nvidia API key. osFoundry discovers Llama-3_3-Nemotron-Super-49B-v1_5 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_3-Nemotron-Super-49B-v1_5 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.
Use Llama-3_3-Nemotron-Super-49B-v1_5 via API
Llama-3_3-Nemotron-Super-49B-v1_5 is also served by hosted API providers — use it via API (BYOK) if you would rather not manage GPUs. That page lists per-provider pricing.
What hardware can run Llama-3_3-Nemotron-Super-49B-v1_5
Llama-3_3-Nemotron-Super-49B-v1_5 runs on a single A100 40GB at Q4 quantisation (~30 GB VRAM with KV-cache headroom). Full-precision inference requires an H200 141GB or 2x A100 80GB at FP16 (~118 GB).
Llama-3_3-Nemotron-Super-49B-v1_5 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_3-Nemotron-Super-49B-v1_5
Is Llama-3_3-Nemotron-Super-49B-v1_5 free to use?
Llama-3_3-Nemotron-Super-49B-v1_5 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_3-Nemotron-Super-49B-v1_5 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_3-Nemotron-Super-49B-v1_5 need?
Approximately 30 GB at Q4 quantisation, or 118 GB at full FP16 precision. Fits on a single A100/H100 80GB.
Can I run Llama-3_3-Nemotron-Super-49B-v1_5 locally?
Yes. Llama-3_3-Nemotron-Super-49B-v1_5 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Llama-3_3-Nemotron-Super-49B-v1_5 best at?
Llama-3_3-Nemotron-Super-49B-v1_5 is well-suited to text generation.
How do I use Llama-3_3-Nemotron-Super-49B-v1_5 in osFoundry?
Paste your nvidia API key in the key dialog (or deploy the open weights for self-hostable models), assign Llama-3_3-Nemotron-Super-49B-v1_5 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by nvidia on July 25, 2025. Source: https://huggingface.co/nvidia/Llama-3_3-Nemotron-Super-49B-v1_5