HuggingFace

Deploying this model locally is quickest when done via Docker.

Make sure to follow the instructions below.

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

🧩 Hash sum → 6c6824ef83049d3d57abe7f7ac8b0963 — Update date: 2026-06-24 Verify Processor: high single-core performance needed for token latency RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components Graphics: 12 GB VRAM minimum required for basic quantization

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.

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• Run Llama-3_3-Nemotron-Super-49B-v1_5 Locally (No Cloud) 2026/2027 Tutorial
• Adjustable damage multiplier trainer script with customizable hotkey combinations
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• Custom camera script for advanced cinematic screenshot capturing tools
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