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Scaling NVFP4 Inference for FLUX.2 on NVIDIA Blackwell Data Center GPUs

In 2025, NVIDIA partnered with Black Forest Labs (BFL) to optimize the FLUX.1 text-to-image model series, unlocking FP4 image generation performance on NVIDIA...

In 2025, NVIDIA partnered with Black Forest Labs (BFL) to optimize the FLUX.1 text-to-image model series, unlocking FP4 image generation performance on NVIDIA Blackwell GeForce RTX 50 Series GPUs. As a natural extension of the latent diffusion model, FLUX.1 Kontext [dev] proved that in-context learning is a feasible technique for visual-generation models, not just large language models (LLMs).

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Delivering Flexible Performance for Future-Ready Data Centers with NVIDIA MGX

The AI boom reshaping the computing landscape is poised to scale even faster in 2026. As breakthroughs in model capability and computing power drive rapid...

The AI boom reshaping the computing landscape is poised to scale even faster in 2026. As breakthroughs in model capability and computing power drive rapid growth, enterprise data centers are being pushed beyond the limits of conventional server and rack architectures. This is creating new pressures on power budgets, thermal envelopes, and facility space. NVIDIA MGX modular reference…

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Enhancing Communication Observability of AI Workloads with NCCL Inspector

When using the NVIDIA Collective Communication Library (NCCL) to run a deep learning training or inference workload that uses collective operations (such as...

When using the NVIDIA Collective Communication Library (NCCL) to run a deep learning training or inference workload that uses collective operations (such as AllReduce, AllGather, and ReduceScatter), it can be challenging to determine how NCCL is performing during the actual workload run. This post introduces the NCCL Inspector Profiler Plugin, which addresses this problem. It offers a way for…

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