NVIDIA Blackwell Ultra Unveiled: Next-Gen Chip Powers AI Factories with Breakthrough Performance, Efficiency, and Scalability

NVIDIA Blackwell Ultra represents a major leap in accelerated computing, designed to power the next era of AI factories and large-scale real-time AI services. As the most advanced member of the Blackwell architecture family, it combines cutting-edge silicon innovations with system-level integration to deliver unmatched performance, scalability, and energy efficiency. At its core, Blackwell Ultra uses a dual-reticle design, integrating two large dies via NVIDIA’s custom High-Bandwidth Interface (NV-HBI), which delivers 10 TB/s of inter-die bandwidth. Built on TSMC’s 4NP process, the GPU contains 208 billion transistors—2.6 times more than the Hopper architecture—while still operating as a single, CUDA-programmable accelerator. This enables massive performance gains without sacrificing the familiar CUDA programming model developers rely on. The GPU features 160 Streaming Multiprocessors (SMs) organized into eight Graphics Processing Clusters (GPCs). Each SM houses advanced fifth-generation Tensor Cores and 256 KB of dedicated Tensor Memory (TMEM), optimized for AI workloads. These Tensor Cores now support dual-thread-block matrix multiply-accumulate (MMA) operations, where paired SMs collaborate on a single computation, reducing redundant memory traffic and boosting efficiency. A key innovation is the introduction of NVFP4, a new 4-bit floating-point format that combines FP8 micro-block scaling with tensor-level FP32 scaling. This enables hardware-accelerated quantization with near-FP8 accuracy and significantly lower error rates. NVFP4 reduces memory footprint by up to 8x compared to FP8 and 3.5x compared to FP16, while delivering 15 petaFLOPS of dense compute—1.5x faster than the base Blackwell GPU and 7.5x faster than Hopper H100/H200. Blackwell Ultra also doubles SFU (Special Function Unit) throughput for attention-layer operations like softmax, which are critical in transformer models. This results in up to 2x faster attention processing, especially beneficial for long-context reasoning tasks where latency has historically been a bottleneck. Memory capacity has been dramatically expanded to 288 GB of HBM3E per GPU—50% more than Blackwell and 3.6x more than H100. This allows trillion-parameter models to run in memory without KV-cache offloading, enabling longer context windows and higher concurrency in inference workloads. The GPU supports fifth-generation NVLink with 1,800 GB/s bandwidth, alongside PCIe Gen 6 (256 GB/s) and NVLink-C2C for seamless CPU-GPU integration. These interconnects ensure efficient scaling across multi-GPU systems and racks. Performance-efficiency improvements are clear: Blackwell Ultra delivers 50% more NVFP4 compute and 50% more memory per chip than Blackwell, pushing the Pareto frontier in both tokens per second per user and tokens per second per megawatt. This makes AI factories more cost-effective and capable of handling massive inference loads. Enterprise features include advanced scheduling, security enhancements, and reliability improvements. The chip also includes specialized engines for AI video and multimodal data processing, supporting modern AI applications. The NVIDIA Grace Blackwell Ultra Superchip—combining a Grace CPU with two Blackwell Ultra GPUs via NVLink-C2C—delivers up to 30 PFLOPS dense and 40 PFLOPS sparse NVFP4 performance, with 1 TB of unified memory. Paired with ConnectX-8 SuperNICs offering 800 GB/s network bandwidth, it forms the foundation of the GB300 NVL72 rack-scale system. Blackwell Ultra maintains full CUDA compatibility while optimizing for next-generation AI frameworks. It marks a pivotal shift from experimental AI to production-scale intelligence, enabling new capabilities in training and inference that were previously impossible. With its breakthroughs in architecture, precision, memory, and interconnects, Blackwell Ultra is setting the standard for AI infrastructure in the era of trillion-token models and real-time intelligence.