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  1. I finally loaded a 120B model - super, onto my . With all the stars aligned and goats sacrificed, I think this is the NVFP4 flavour. I'm using it to review patches I made earlier for evaluation.

    So far I'm blown away by how _fast_ it is, I'm seeing ~20-25 tokens per second.

    It's too soon if this is going to replace my go-to model (qwen3.6-35B-A3B) but I'm looking forward to using during my day job tasks.

    I run two models, one on and one more on the spark. A/B :)

  2. NVIDIA already controls the hardware most AI models run on. Now they want a say in which models run on that hardware too.

    Nemotron 3 Nano Omni is their latest move in that direction. It’s an omnimodal model that can handle text, images, video, and audio natively in one architecture.

    The 30B total parameter count with 3B active makes it approachable for serious deployment without needing heavy hardware. firethering.com/nemotron-3-nan

    #ai #llms #technews #nemotron3 #nvidia #news #trending #genai

  3. Nemotron 3 Super pushes the frontier with 40 M supervised & alignment samples, leveraging a Mamba‑Transformer backbone and Mixture‑of‑Experts scaling. The model shows stronger agent reasoning, RL‑based fine‑tuning, and tighter AI alignment. Dive into the details to see how this LLM reshapes open‑source AI. #Nemotron3 #MixtureOfExperts #AIAlignment #SupervisedFineTuning

    🔗 aidailypost.com/news/nemotron-