1/ NVIDIA shipped Nemotron 3 Ultra today， a fully open 550B model with 55B active params， with the weights， training data， and complete recipe all released openly. That alone is rare at this scale.

The headline however actually is speed. Ultra is a hybrid Mamba-Attention MoE， an architecture built for fast decoding and a light memory footprint over long contexts， and NVIDIA clocks it at roughly 6x （！） the throughput of comparable open models on long-output agent workloads while holding the same accuracy.

That's a serious engineering result， and it's aimed exactly where the industry is heading： autonomous agents that run long， multi-turn tasks where throughput per GPU is what actually costs money.

It was pre-trained in 4-bit （NVFP4） across 20T tokens， the largest stable run of its kind shown to date. And the post-training introduces MOPD， where ten-plus specialist teacher models distill their skills into the student on its own rollouts， sometimes pushing it past the teachers themselves.

The interesting aspect：This is a frontier-class model you can fully reproduce.