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Nemotron 3.5 Super VL runs locally with 128GB RAM, bypassing Blackwell GPU needs

NVIDIA's Nemotron 3.5 Super VL, a 120B parameter vision-language model, can be run locally with approximately 128GB of RAM, though GPU power is less critical than memory capacity. While NVIDIA's official deployment targets include high-end hardware like DGX Spark or GB200, community conversions have made the model accessible on systems with less specialized GPUs. The model offers a 1M token context window and supports text, image, and video inputs, showing significant improvements in reasoning and agentic tasks compared to its predecessor, Nemotron 3 Super, though some benchmarks like multilingual knowledge saw a decrease. AI

IMPACT Enables local deployment of advanced vision-language models on consumer hardware, reducing reliance on specialized GPUs.

RANK_REASON Article discusses running a specific model locally, focusing on hardware requirements and community-driven optimizations rather than a new model release from a frontier lab.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Nemotron 3.5 Super VL runs locally with 128GB RAM, bypassing Blackwell GPU needs

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32 / 100
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Tool
Article discusses running a specific model locally, focusing on hardware requirements and community-driven optimizations rather than a new model release from a frontier lab.
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model release, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Alan West ·

    How to Run Nemotron 3.5 Super VL Locally: You Need 128GB, Not a Blackwell GPU

    <p>Can you run Nemotron 3.5 Super VL locally without a Blackwell GPU? Yes, if you have roughly 128 GB of memory. The GPU generation matters much less than that number.</p> <p>NVIDIA released the model on October 15: a 120B vision-language MoE with 12B active parameters. The headl…