Mohammad Shoeybi

AV-Flamingo outperforms existing models on complex audio-visual tasks, revealing that size isn't everything when it comes to reasoning capabilities.

Audex achieves state-of-the-art audio understanding and generation while maintaining the reasoning prowess of its text-only foundation, all through a unified architecture.

Achieving 2.42X faster generation without sacrificing quality, Nemotron-TwoTower redefines the efficiency of language modeling.

Achieving six times the inference throughput of current LLMs while maintaining accuracy, Nemotron 3 Ultra redefines performance benchmarks for agentic reasoning tasks.

Nemotron 3 Super proves you can achieve comparable accuracy to existing 120B models, but with significantly higher inference throughput, by combining Mamba, Attention, and Mixture-of-Experts.

Audio-language models can now reason about 30-minute-long audio clips with timestamp-grounded intermediate steps, unlocking a new level of fine-grained understanding.

A 30B MoE model can now achieve Gold Medal-level performance in IMO, IOI, and ICPC, rivaling frontier models with 20x more parameters.

Current multimodal models are surprisingly bad at understanding long, complex videos, struggling to integrate audio, visual, and text cues even for basic reasoning tasks.

Training trillion-parameter Mixture-of-Experts models just got a whole lot faster: Megatron Core now achieves >1 PFLOP/GPU on NVIDIA's latest hardware.

Forget hand-crafted datasets: a new synthetic data pipeline lets smaller LLMs beat giants at terminal tasks.