NVIDIA's Nemotron family of open AI models for generative AI and agentic applications, including multimodal members.
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NVIDIA released Nemotron 3.5 Embed and Rerank models with document-image support through Sentence Transformers. NVIDIA reports reranking raises its ViDoRe v3 image-and-text result from 58.82 to 67.56 nDCG@10.
PhoneLLM Mini and Max are Nemotron fine-tunes claiming per-call time to first answer token below 100ms and 200ms, respectively. Those figures exclude network and tool latency; the production P95 target is below 600ms.
Nemotron 3.5 Super VL has 120B total parameters, 12B active per token and a 1M-token context window. Ollama and Factory added the model, with Factory reporting improved tool-call parallelism.
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.
AI21 says its pipeline routes exploration, extraction, and patching across model tiers and reaches 80.8% on SWE-Bench Pro at $5.99 per task. Other workflows use critic agents, readable harnesses, Fugu/Nemotron routing, and scheduled Gemini agents.
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.