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GB300 NVL72 at a Glance

1440 PFLOPS

FP4 Tensor Core Performance (with sparsity)

20 TB

Total GPU Memory Across 72 GPUs

576 TB/s

GPU Memory Bandwidth

50×

AI Factory Output Uplift vs. Hopper-Based Platforms

What is the NVIDIA GB300 NVL72?

The NVIDIA GB300 NVL72 is the successor to the GB200 NVL72, built on NVIDIA's Blackwell Ultra architecture. Unlike conventional multi-server GPU clusters, the NVL72 architecture treats an entire rack as a single unified compute node — eliminating the inter-node communication latency that traditionally bottlenecks large-scale AI workloads.

Here is what makes this a fundamentally different class of AI GPU server:

  • 72 NVIDIA Blackwell Ultra GPUs (B300) and 36 NVIDIA Grace CPUs occupy a single rack
  • All 72 GPUs are interconnected via fifth-generation NVLink at 130 TB/s of NVLink bandwidth, enabling zero-overhead GPU-to-GPU communication
  • Each Blackwell Ultra GPU carries 288 GB of HBM3e memory — 1.5× more than its Blackwell predecessor — with 8 TB/s per-GPU bandwidth
  • The rack is fully liquid-cooled, engineered for sustained high-density operation
  • Integrated NVIDIA Grace CPUs eliminate CPU-GPU transfer bottlenecks inherent in traditional x86-based server designs

The result: a coherent, rack-scale AI infrastructure platform that behaves like one massive supercomputer — not a cluster of boxes.

WhatistheNVIDIAGB300NVL72?

Build Your AI Factory
with NVIDIA GB300 NVL72

Unlock 1,440 PFLOPS of AI compute, 20TB of GPU memory, and unmatched performance for LLM training, reasoning inference, and enterprise AI deployments.

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Technical Specifications
NVIDIA GB300 NVL72 Technical Specifications

Specification Value
Configuration 72 NVIDIA Blackwell Ultra GPUs (B300) + 36 NVIDIA Grace CPUs
GPU Architecture NVIDIA Blackwell Ultra (B300)
GPU Memory per GPU 288 GB HBM3e
Total GPU Memory 20 TB HBM3e
GPU Memory Bandwidth Up to 576 TB/s (aggregate across 72 GPUs)
FP4 Tensor Core Performance 1440 PFLOPS (with sparsity) | 1080 PFLOPS (without sparsity)
FP8 / FP6 Tensor Core 720 PFLOPS
FP16 / BF16 Tensor Core 360 PFLOPS
TF32 Tensor Core 180 PFLOPS
FP32 6 PFLOPS
FP64 / FP64 Tensor Core 100 TFLOPS
INT8 Tensor Core 24 POPS
NVLink Generation Fifth-Generation NVLink
NVLink Bandwidth 130 TB/s (rack-level)
CPU Architecture 36 NVIDIA Grace CPUs (Arm Neoverse V2)
CPU Core Count 2,592 Arm Neoverse V2 cores
CPU Memory 17 TB LPDDR5X
CPU Memory Bandwidth 14 TB/s
Total Fast Memory (CPU + GPU) 37 TB
Networking NVIDIA ConnectX-8 SuperNIC — 800 Gb/s per GPU
Network Fabric Options NVIDIA Quantum-X800 InfiniBand | NVIDIA Spectrum-X Ethernet
Cooling Fully liquid-cooled rack-scale design
Management NVIDIA Mission Control software
Form Factor Rack-scale integrated system (NVL72 form factor)

Inside the Architecture: What Powers the GB300 NVL72

NVIDIA Blackwell Ultra GPU (B300)

The Blackwell Ultra GPU is the computational engine of the GB300 NVL72. Compared to the standard Blackwell GPU, Blackwell Ultra delivers 1.5× more dense FP4 Tensor Core FLOPS and 2× higher attention-layer performance — the two metrics that matter most for test-time scaling inference and chain-of-thought AI reasoning models. Each GPU carries 288 GB of HBM3e memory, enabling it to hold and serve massive model shards with sub-millisecond latency.

Fifth-Generation NVLink — The Unified Fabric

The fifth-generation NVLink interconnect is what transforms 72 individual GPUs into a single compute domain. At 130 TB/s of rack-level NVLink bandwidth, it provides the data throughput needed to keep all 72 GPUs fed with activations, gradients, and key-value cache data simultaneously. For AI reasoning workloads — where models repeatedly attend to long context windows — this coherent, low-latency fabric is the difference between production-grade throughput and a bottlenecked cluster.

NVIDIA Grace CPU — Native CPU-GPU Integration

The 36 NVIDIA Grace CPUs are based on the Arm Neoverse V2 architecture and are natively co-designed with the GPU fabric. Each Grace CPU delivers 2× the energy efficiency of comparable x86 server processors. With 2,592 Arm cores and 17 TB of LPDDR5X CPU memory running at 14 TB/s, the Grace subsystem handles data ingestion, orchestration, and preprocessing without becoming a bottleneck — a persistent limitation of GPU clusters built around legacy x86 architectures.

NVIDIA ConnectX-8 SuperNIC — 800 Gb/s Per GPU

Each GPU in the GB300 NVL72 is connected to the network through NVIDIA's ConnectX-8 SuperNIC, providing 800 Gb/s of network bandwidth per GPU. This supports both NVIDIA Quantum-X800 InfiniBand and Spectrum-X Ethernet, giving operators flexibility in fabric selection. The SuperNIC delivers best-in-class RDMA capabilities, enabling zero-copy data transfers and the low-latency collective communications that distributed AI training depends on.

Full Rack Liquid Cooling

72 Blackwell Ultra GPUs in a single rack generate heat densities that air cooling cannot handle reliably. The GB300 NVL72's integrated liquid cooling is not an afterthought — it is a foundational design requirement. Liquid cooling enables the sustained, high-utilization operation that AI factory workloads demand, without thermal throttling or performance degradation under sustained load.

NVIDIA Mission Control — AI Factory Operating Layer

NVIDIA Mission Control is the software management layer designed specifically for Grace Blackwell data centers. It streamlines workload scheduling, infrastructure monitoring, and operational automation — giving operators hyperscale-level efficiency without hyperscale-level headcount. For GB300 GPU Cloud deployments, Mission Control provides the operational intelligence to maximize GPU utilization across training and inference workloads.

What Can You Build on the NVIDIA GB300 NVL72?

Large-Scale Foundation Model Training

Large-Scale Foundation Model Training

Training frontier-scale LLMs — models with hundreds of billions to trillions of parameters — demands a compute substrate where all GPUs can communicate freely, at high bandwidth, without multi-node overhead. The GB300 NVL72's 72-GPU unified domain with 130 TB/s NVLink bandwidth makes it the natural platform for training at the frontier. Researchers no longer need to spend weeks engineering around cluster communication bottlenecks.

AI Reasoning Inference & Test-Time Scaling

AI Reasoning Inference & Test-Time Scaling

AI reasoning models — think chain-of-thought, multi-step problem solving, long-context document analysis — are compute-hungry at inference time, not just training time. The Blackwell Ultra GPU's 2× attention-layer acceleration and 288 GB per-GPU memory directly address the two bottlenecks in reasoning inference: compute throughput and KV cache capacity. The GB300 NVL72 is the purpose-built platform for production-grade AI reasoning at scale.

High-Throughput LLM Serving

High-Throughput LLM Serving

Serving LLMs to thousands of concurrent users requires sustained memory bandwidth and the ability to hold massive model weights in fast memory. With 20 TB of HBM3e across 72 GPUs and 576 TB/s of aggregate bandwidth, the GB300 NVL72 can hold and serve models that simply cannot fit — or run efficiently — on smaller GPU configurations. For enterprises deploying proprietary or fine-tuned LLMs at scale, this is the platform that eliminates queueing, latency spikes, and throughput ceilings.

Hyperscale AI Factory Infrastructure

Hyperscale AI Factory Infrastructure

Cloud providers, national AI compute programs, and large enterprises building dedicated AI compute environments need infrastructure that runs at high utilization, continuously, without thermal or power management issues. The GB300 NVL72's liquid cooling and rack-scale integration are designed for exactly this operating profile — sustained, dense, reliable.

Multimodal & Generative AI at Scale

Multimodal & Generative AI at Scale

Video generation, image synthesis, and multimodal models that combine text, vision, and audio require both massive compute throughput and large memory capacity simultaneously. The GB300 NVL72 provides both in a single cohesive system, removing the memory-bandwidth tradeoffs that constrain multimodal workloads on smaller GPU configurations.

HPC & Scientific Simulation

HPC & Scientific Simulation

Beyond AI, the GB300 NVL72's FP64 capability (100 TFLOPS) and massive parallel compute make it a serious platform for climate modeling, molecular dynamics, computational fluid dynamics, and other HPC workloads that benefit from GPU acceleration.

Performance: What 50× Improvement Actually Means

Performance: What 50× Improvement Actually Means

NVIDIA benchmarks comparing GB300 NVL72-based AI factories against NVIDIA Hopper-based platforms show:

10× improvement in user responsiveness (tokens per second per user) for AI reasoning inference
5× improvement in throughput efficiency (tokens per second per megawatt)
50× overall AI factory output uplift when combined with Quantum-X800 InfiniBand or Spectrum-X Ethernet, ConnectX-8 SuperNICs, and NVIDIA Mission Control

In practical terms: a GB300 NVL72-based AI factory running DeepSeek R1-scale reasoning models (32K input, 8K output context) at FP4 precision with Dynamo disaggregation delivers output performance that would require 50 equivalent Hopper-based racks to match — at a fraction of the power footprint.

This is not incremental improvement. The GB300 NVL72 is a step-change in AI infrastructure economics.

Why Access NVIDIA GB300 NVL72 Through Cyfuture AI?

Cyfuture AI is India's premier high-performance GPU as a service and cloud infrastructure provider , with a decade of enterprise infrastructure experience and a track record across banking, research, defense, and enterprise sectors. Here is what you get when you access GB300 GPU hosting through Cyfuture AI:

01

Immediate Access to Validated GB300 NVL72 Infrastructure

Skip the 12–18 month procurement and deployment cycle for a rack-scale AI system. Cyfuture AI gives enterprises immediate access to NVIDIA GB300 NVL72 GPU Server capacity — fully configured, liquid-cooled, and ready for production workloads. No procurement delays. No integration risk.

02

GB300 GPU as a Service — Flexible Compute Models

Access the GB300 NVL72's compute through Cyfuture AI's GB300 GPU as a Service model. Provision rack-scale AI capacity sized to your workload — from dedicated single-rack deployments to multi-rack AI factory configurations. You get predictable, transparent pricing without the capital commitment of owning a rack-scale system.

03

Enterprise-Grade AI Infrastructure

Cyfuture AI's infrastructure is built to enterprise and sovereign standards — ISO-certified data centers, redundant power and cooling, 99.99% uptime SLA, and dedicated private networking. Your GB300 AI server workloads run on infrastructure that meets the reliability requirements of banking, healthcare, and government deployments.

04

Full-Stack AI Platform Integration

The NVIDIA GB300 NVL72 GPU Server on Cyfuture AI connects seamlessly into Cyfuture's broader AI platform — including GPU Clusters, Inferencing as a Service, Fine-Tuning, and AI Model Library. Start with raw compute and graduate to fully managed AI services as your workloads mature.

05

24×7 Expert Support & White-Glove Deployment

From initial consultation and workload profiling through deployment, optimization, and ongoing operations, Cyfuture AI's AI infrastructure team is with you at every stage. Our experts understand both the hardware — rack-scale liquid-cooled AI systems — and the software stack running on it, including PyTorch, TensorFlow, NVIDIA Triton, and NVIDIA AI Enterprise.

06

Sovereign AI Compute for India

For Indian enterprises and government organizations, Cyfuture AI offers GB300 GPU Cloud capacity hosted in India — giving you the compute power of the world's most advanced AI GPU server platform with the data residency and sovereignty assurance your compliance requirements demand.

WhyAccessNVIDIAGB300NVL72ThroughCyfutureAI

Power the Next
Generation of AI Reasoning

Deploy the NVIDIA GB300 NVL72 to accelerate chain-of-thought reasoning, long-context inference, and frontier AI models with unprecedented scale and performance.

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H200 GPUs

Voices of Innovation: How We're Shaping AI Together

We're not just delivering AI infrastructure-we're your trusted AI solutions provider, empowering enterprises to lead the AI revolution and build the future with breakthrough generative AI models.

KPMG optimized workflows, automating tasks and boosting efficiency across teams.

H&R Block unlocked organizational knowledge, empowering faster, more accurate client responses.

TomTom AI has introduced an AI assistant for in-car digital cockpits while simplifying its mapmaking with AI.

NVIDIA GB300 NVL72 vs. GB200 NVL72
Key Differences

Specification GB300 NVL72 (Blackwell Ultra) GB200 NVL72 (Blackwell)
GPU Architecture Blackwell Ultra (B300) Blackwell (B200)
GPU Memory per GPU 288 GB HBM3e 192 GB HBM3e
Total GPU Memory 20 TB 13.5 TB
FP4 PFLOPS (w/ sparsity) 1440 PFLOPS ~960 PFLOPS
Attention Performance 2× vs. Blackwell Baseline
FP4 Compute Density 1.5× vs. Blackwell Baseline
NVLink Bandwidth 130 TB/s 130 TB/s
Primary Use Case AI Reasoning / Test-Time Scaling LLM Training & Inference
AI Factory Uplift vs. Hopper 50× ~30×

Supported Frameworks & Software Stack

The NVIDIA GB300 NVL72 is fully supported by the NVIDIA AI software ecosystem. Cyfuture AI's GB300 AI Server deployments support:

NVIDIA AI Enterprise

NVIDIA AI Enterprise

full suite of enterprise AI software, support, and security

NVIDIA Triton Inference Server

NVIDIA Triton Inference Server

optimized model serving for production inference

NVIDIA NeMo

NVIDIA NeMo

large language model development and fine-tuning framework

PyTorch & TorchScript

PyTorch & TorchScript

industry-standard deep learning framework

TensorFlow & JAX

TensorFlow & JAX

alternative DL frameworks with full GPU acceleration

RAPIDS

RAPIDS

GPU-accelerated data science and analytics

CUDA 12 and CUDA-X libraries

CUDA 12 and CUDA-X libraries

full acceleration stack for custom workloads

NVIDIA Mission Control

NVIDIA Mission Control

AI factory management and workload orchestration

vLLM, DeepSpeed, Megatron-LM

vLLM, DeepSpeed, Megatron-LM

distributed training and serving optimization

NVIDIA Dynamo

NVIDIA Dynamo

disaggregated inference for test-time scaling workloads

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FAQs: NVIDIA GB300

The power of AI, backed by human support

At Cyfuture AI, we combine advanced technology with genuine care. Our expert team is always ready to guide you through setup, resolve your queries, and ensure your experience with Cyfuture AI remains seamless. Reach out through our live chat or drop us an email at [email protected] - help is only a click away.

The NVIDIA GB300 NVL72 is a rack-scale AI system built on NVIDIA's Blackwell Ultra architecture. It integrates 72 NVIDIA B300 GPUs and 36 NVIDIA Grace CPUs into a single, fully liquid-cooled compute platform connected by fifth-generation NVLink. It is designed for AI reasoning inference, large-scale LLM training, and hyperscale AI factory deployments.

A standard GPU server contains 4–8 GPUs in a single chassis. The GB300 NVL72 is a full rack containing 72 GPUs that operate as a single unified compute node. There are no inter-server communication boundaries — all 72 GPUs share memory and communicate at 130 TB/s via NVLink, enabling model parallelism and collective operations that are impossible on conventional multi-server clusters.

NVIDIA Blackwell Ultra (the B300 GPU) is the upgraded variant of the Blackwell architecture. It delivers 1.5× more FP4 Tensor Core FLOPS and 2× higher attention-layer performance compared to the standard Blackwell GPU (B200), along with 288 GB of HBM3e memory per GPU — 1.5× more than its predecessor. These improvements are targeted specifically at the demands of AI reasoning and test-time scaling inference.

Test-time scaling refers to spending more compute at inference time to improve model output quality — techniques like chain-of-thought reasoning, self-reflection, and multi-step problem solving. These approaches dramatically increase the per-query compute requirement compared to standard inference. The GB300 NVL72's higher attention throughput and larger memory capacity make it the purpose-built platform for production deployment of AI reasoning models at scale.

Yes. Cyfuture AI supports both single-rack GB300 NVL72 deployments and multi-rack AI factory configurations connected via NVIDIA Quantum-X800 InfiniBand or Spectrum-X Ethernet. Multi-rack configurations are ideal for enterprises training frontier-scale models or building dedicated AI compute platforms.

NVIDIA GB300 GPU pricing through Cyfuture AI is customized based on deployment configuration, duration, and workload requirements. Contact our sales team for current NVIDIA GB300 GPU pricing and a configuration proposal tailored to your needs.

Yes. Cyfuture AI operates enterprise-grade, India-located data centers with ISO certification, redundant power and cooling, and compliance with Indian data sovereignty requirements. Enterprises in banking, healthcare, defense, and government sectors can access GB300 GPU Cloud capacity with the assurance of in-country data residency.

Cyfuture AI provides end-to-end support for NVIDIA GB300 NVL72 GPU Server deployments: workload profiling and configuration consulting, deployment and integration, framework optimization (PyTorch, TensorFlow, Triton), and 24×7 operational support with defined SLAs. Our team includes AI infrastructure engineers with hands-on experience on Blackwell and Grace Blackwell systems.

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