NVIDIA’s Nemotron 3 Super is a follow-up development from GTC 2026 (March 16-19), and it represents something specific: NVIDIA competing not just as a hardware provider but as a full-stack enterprise AI player at the model layer.
According to NVIDIA, Nemotron 3 Super uses a hybrid Mixture-of-Experts architecture with 120 billion total parameters and 12 billion active per forward pass. That active parameter count is the relevant number for inference cost and latency, 12 billion active parameters is efficient for a model of this size. NVIDIA announced the model approximately March 11, ahead of the GTC conference where it was showcased.
On benchmarks: according to NVIDIA’s internal evaluation, Nemotron 3 Super scores 60.47% on SWE-Bench Verified and 91.75% on the RULER long-context benchmark (1M token context). These are vendor-reported figures. SWE-Bench is an established external benchmark, but the score here comes from NVIDIA itself, not an independent assessor. Independent evaluation via Epoch AI is pending.
Per industry coverage, Anaconda reportedly announced expanded integration with NVIDIA, making the Nemotron model family available in Anaconda’s AI Catalyst for enterprise governance environments. This claim rests on a single analyst source and should be treated accordingly until confirmed through official Anaconda or NVIDIA channels.
A note on scope: Nemotron 3 Super is a coding-specialized LLM. It’s distinct from NeMoClaw, NVIDIA’s open-source security agent stack, which was covered separately. Different product, different use case.