June 29, 2026

How to Launch Llama-3_3-Nemotron-Super-49B-v1_5 For Low VRAM (6GB/8GB)

How to Launch Llama-3_3-Nemotron-Super-49B-v1_5 For Low VRAM (6GB/8GB)

The fastest way to get this model running locally is via Docker.

Please follow the instructions listed below to get started.

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

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

🧮 Hash-code: 1c940a6b721ae452a022c555e8fd1136 • 📆 2026-06-22



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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