Nemotron

Meta says AIRA3 placed eighth among roughly 4,000 teams in a live NVIDIA Kaggle competition. The system used many long-running agents to fine-tune a 30B Nemotron model on a private test set.

Julius Jitsev said SOOFI removed GPQA and its capability index after feedback but still compared against Nemotron 3 Nano using benchmarks seen in training. He argued the remaining English and German scores are compromised.

A German consortium released the small SOOFI sovereign base model trained on 27T tokens. Analysts said it reuses Nemotron 3 Nano architecture and many hyperparameters with a changed data mix, and benchmarks drew criticism for overstating capability versus Qwen and Nemotron.

NVIDIA shipped Nemotron 3 Ultra, a 550B/55B-active hybrid Mamba-Transformer MoE with open weights, data, and recipe, plus broad runtime and host support. It matters because the model pairs frontier open benchmarks with immediate agent-serving options, though local use still needs heavy quantization or large-memory hardware.

NVIDIA opened Nemotron 3 Nano Omni, a 30B-A3B model for text, image, audio, and video, with day-one serving support. That lets teams run one open model for perception-heavy agents instead of stitching separate components.

NVIDIA released Nemotron 3 Super, a 120B open model with 1M-token context and a hybrid architecture tuned for agent workloads, then landed it in Perplexity and Baseten. Try it if you need an open-weight long-context option that is already available in hosted stacks.