How to Deploy Llama-3_3-Nemotron-Super-49B-v1_5 Locally via LM Studio 5-Minute Setup

How to Deploy Llama-3_3-Nemotron-Super-49B-v1_5 Locally via LM Studio 5-Minute Setup

Running this model locally is fastest when deployed through Docker.

Use the instructions provided below to complete the setup.

The installer automatically pulls the model (could be multiple GBs).

The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.

🧩 Hash sum → fbcd66d23b3e824e6a44132fc990d9cf — Update date: 2026-06-25



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

The Llama-3_3-Nemotron-Super-49B-v1_5 is a large language model designed for both research and commercial applications, featuring a massive 49‑billion parameter architecture. It delivers state‑of‑the‑art performance on reasoning, coding, and multilingual tasks, achieving top scores on standard benchmarks such as MMLU and HumanEval. Thanks to optimized transformer layers and a sparse attention mechanism, the model maintains low inference latency while preserving high accuracy. The model is optimized for deployment on modern GPU clusters, offering scalable throughput and reduced memory footprint through quantization support. These characteristics make it a compelling choice for enterprises seeking high‑performance AI solutions without compromising on cost or speed.

Parameters 49 B
Context length 8 K tokens
Training data ≈1.5 TB text
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