AINewsnow

NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning

Always-on agents are taking on longer, more complex enterprise workflows. A single request can involve reading a document, checking information across sources,...

Read the full story at NVIDIA Technical Blog ↗

Timeline · 4 reports

  1. 2026-10-16 12:09 · r/LocalLLM
    Has anyone tried this Bolt 74B-A9B 24GB on a 5090 yet?
  2. 2026-10-16 07:39 · r/LocalLLM
    NVIDIA Nemotron 3.5 Bolt 74B A9B 24GB GGUF
  3. 2026-10-15 20:12 · r/machinelearningnews
    NVIDIA releases Nemotron 3.5 Super VL (120B-A12B, open weights, 1M ctx, image + video) and Bolt 74B-A9B that fits in 24GB
  4. 2026-10-15 18:01 · NVIDIA Technical Blog
    NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning

More stories

  1. Academic history research agent on 16GB vRAM, context important — r/LocalLLM
  2. QUASAR 4-bit QAT checkpoints for Qwen3.5, Gemma 4 and Muse Glimmer: closer to BF16 than Google’s and NVIDIA’s 4-bit releases — r/LocalLLaMA
  3. Notes from a 2 AM On-Call: When llama-swap's Model Reload Hit a 30s Timeout Wall — DEV Community — Machine Learning
  4. Round 3: Tested 128K context on a 3090 with real code (Django) and a novel. Finding one thing is solid, counting is hopeless — r/LocalLLM
  5. Qwen Ships Qwen3-VL 8B Locally, Seeing Images and Video in 5 GB — AlphaSignal
  6. Efforts to upstream adaptive MTP depth to llama.cpp abandoned — r/LocalLLM
  7. New quant types suggested: IQ2_K, IQ3_K, IQ4_K, IQ5_K and IQ6_K — r/LocalLLaMA
  8. Has anyone used EXO in x86 machines, or am I just better off using llama.cpp or dllama? — r/LocalLLM

Get the daily brief of stories like this at 6:30 every morning →