NVIDIA's SANA-WM generates 60-second, 720p video from a single image and a camera trajectory — on a single GPU. The open-source 2.6B-parameter model achieves 36× higher throughput than prior open-source world models and ships under Apache 2.0.
NVIDIA's NVlabs released cuda-oxide v0.1.0 on May 7, an experimental compiler that takes standard Rust and emits NVIDIA PTX directly — no CUDA C++, no DSLs, no foreign language bindings. The pipeline goes through a custom rustc codegen backend and a Rust-native MLIR-like IR called Pliron. Alpha-stage and Linux-only, but it signals where NVIDIA thinks GPU kernel development might eventually land.
NVIDIA released Ising on April 14: two open-source AI model families for quantum computer infrastructure. A 35B VLM reads measurement data from quantum processors and infers calibration adjustments in hours instead of days. A 3D CNN family handles real-time quantum error correction 2.5× faster and 3× more accurately than the current open-source standard. The approach positions AI as the control plane for quantum hardware.
MLPerf Inference v6.0 results show NVIDIA achieved a 2.77x throughput improvement on DeepSeek-R1 since the v5.1 results six months ago — on the same B200 hardware. The gains came entirely from software: disaggregated prefill/decode serving, kernel fusion, pipelined execution, and multi-token prediction. Token cost dropped to $0.30/M. It's a useful reminder that the current inference scaling curve has two axes, and software is doing more work than it gets credit for.