NVIDIA

Kimi K3 open weights need roughly 1.5TB of VRAM, which does not fit on a B200 node. That forces a real hardware decision: B300, two B200 nodes, or AMD's MI355X. Here is the head-to-head with verified specs, the Wafer benchmark, and what it costs per token.

Nvidia, Microsoft, Meta, OpenAI, and 30+ signatories published an open letter arguing that open-weight AI models are essential to American AI leadership. The letter draws battle lines that divide Silicon Valley.

A practical walkthrough of Nemotron 3 Super: latent mixture of experts, hybrid Mamba transformer architecture, 1M context, reasoning modes, and the code you actually need to run it on NVIDIA hardware.

NVIDIA's Nemotron 3 Super combines latent mixture of experts with hybrid Mamba architecture - 120B total parameters, 12B active per token, 1M context, and up to 4x more experts at the same cost.

NVIDIA's Nemotron Nano 2 VL delivers vision-language capabilities at a fraction of the computational cost. This 12-billion-parameter open-source model processes videos, analyzes documents, and reas...

NVIDIA's Nemotron Nano 9B V2 delivers something rare: a small language model that doesn't trade capability for speed. This 9B parameter model outperforms Qwen 3B across instruction following, math,...