Llama-3_3-Nemotron-Super-49B-v1_5 Locally via Ollama 2 For Low VRAM (6GB/8GB) Complete Walkthrough

For the fastest local setup of this model, Docker is the best choice.

Follow the sequence of steps detailed below.

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

You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.

📘 Build Hash: b906c897cadba2b4f376104edc43249c • 🗓 2026-06-25
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  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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