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AI CURATED HOT STORY · 10/15/2026

NVIDIA Open-Sources Nemotron 3.5 Super VL: Doubling Intelligence via 120B MoE and NVFP4 Quantization for Full-Stack Edge Deployment

5 reports archived5 independent sourcesupdated 10/16/2026, 00:09:44
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NVIDIA has open-sourced Nemotron 3.5 Super VL, a 120B-parameter Mixture-of-Experts (MoE) multimodal model that tops the US open-weight leaderboard with an intelligence score of 26.5. The model doubles its predecessor's intelligence while reducing output tokens by ~60%, significantly enhancing inference efficiency. It supports a 1M context window and achieves near-lossless performance under NVFP4 quantization, trailing BF16 by only 0.1 points.

Designed for persistent enterprise agents, Super VL integrates text, image, document, and video understanding, delivering up to 5x higher throughput on single GPUs compared to similar-scale models. The accompanying Bolt series—Bolt 74B-A9B and Bolt E4B—targets local workstations (24GB VRAM) and edge devices (4GB VRAM), respectively. Notably, Bolt 74B-A9B approaches flagship performance with just one-seventh the parameters, offering exceptional cost-efficiency.

This release completes NVIDIA's full-stack open model matrix, spanning from data centers to edge devices. By enabling post-training customization via the NeMo toolkit, it empowers developers to deploy complex reasoning agents without compromising between capability and deployability, reshaping the landscape for cloud-edge collaborative AI infrastructure.

LATEST/Nemotron 3.5 Super VL is now live on OpenRouter, supporting 1M context windows and GUI video understanding, marking its entry into production testing. Meanwhile, the Bolt series refines edge deployment strategies, allowing developers to use the NeMo toolkit for domain-specific post-training.

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Total 5 reports · Latest first
  1. The DecoderT2·85 pts
    • Nemotron 3.5 Super VL uses a MoE architecture with 120B total parameters but activates only 12B per token, balancing performance and efficiency.
    • Designed specifically for 'always-on' enterprise agents, it natively supports multimodal reasoning across text, images, documents, and video.
    • Companion Bolt 74B-A9B and Bolt E4B models target local workstations (24GB VRAM) and edge devices (4GB VRAM), respectively.
  2. Artificial Analysis (@ArtificialAnlys)T1·86 pts
    • Nemotron 3.5 Super VL leads US open-weight models with an Intelligence Index score of 26.5, surpassing competitors like Thinking Machines' Inkling Small.
    • The new model doubles the intelligence of its predecessor while reducing output tokens per task by approximately 60%, enhancing inference efficiency.
    • NVFP4 quantized weights show near-lossless performance, scoring within 0.1 points of BF16, validating low-precision formats for maintaining capability.
    • The newly launched Bolt 74B-A9B model achieves a score of 21 with only one-seventh of the parameters of the flagship Ultra, offering high cost-efficiency.
  3. OpenRouter (@OpenRouter)T1·68 pts
    • NVIDIA Nemotron 3.5 Super VL is an open-source 120B-A12B multimodal model now available on OpenRouter.
    • The model supports a 1 million token context window, optimized for long-running agent scenarios requiring complex reasoning.
    • It features cross-modal capabilities handling text, images, documents, GUI screenshots, and video, suitable for automation tasks.
  4. IT之家 · 智能时代T2·84 pts
    • Nemotron 3.5 Super VL uses an MoE architecture with 120B total but only 12B active parameters, balancing capability and efficiency.
    • Optimized for multi-step AI agent tasks, achieving up to 5x higher throughput than comparable open models on a single GPU.
    • Integrates text, image, document, and video understanding, supporting enterprise-level post-training customization via the NeMo toolkit.
  5. NVIDIA BlogT1·78 pts
    • Nemotron 3.5 Super VL is a 120B-parameter open model optimized for highest accuracy and fastest task completion in always-on agents.
    • Two new edge models, Bolt 74B-A9B (24GB) and Bolt E4B (4GB), are introduced to balance intelligence and speed for local workloads and conversational agents.
    • The update completes the Nemotron family, joining Lightning (throughput) and Ultra (reasoning) to cover the full range of agent deployment scenarios.