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⚡ NVIDIA DGX B200 vs GB200 NVL72

NVIDIA DGX B200 vs NVIDIA GB200 NVL72 compared across 3 matched specifications — scores, the full spec table and a verdict.

NVIDIA DGX B200 8x Blackwell GPU AI supercomputer for enterprise generative AI
NVIDIA DGX B200
NVIDIA DGX
8.2
Overall Score
Best for: Air-cooled data centres adding Blackwell AI capacity one 8-GPU node at a time.
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NVIDIA GB200 NVL72 rack-scale liquid-cooled AI system — 72 Blackwell GPUs and 36 Grace CPUs
NVIDIA GB200 NVL72
NVIDIA DGX
9.2
Overall Score
Best for: Liquid-cooled facilities running trillion-parameter models that need a single 72-GPU NVLink domain.
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NVIDIA DGX B200 vs GB200 NVL72: performance overview

Scores based on quantifiable specification values (1-10 scale)

ComputeMemoryNetworkingPower / CoolingEcosystem
NVIDIA DGX B200
NVIDIA GB200 NVL72
Compute
NVIDIA DGX B200
8.0
NVIDIA GB200 NVL72
10.0
Memory
NVIDIA DGX B200
8.0
NVIDIA GB200 NVL72
10.0
Networking
NVIDIA DGX B200
8.0
NVIDIA GB200 NVL72
10.0
Power / Cooling
NVIDIA DGX B200
8.0
NVIDIA GB200 NVL72
7.0
Ecosystem
NVIDIA DGX B200
9.0
NVIDIA GB200 NVL72
9.0

Detailed Specifications

Specification
NVIDIA DGX B200
NVIDIA DGX
NVIDIA GB200 NVL72
NVIDIA DGX
At a Glance
Brand & ModelNVIDIA DGX B200NVIDIA GB200 NVL72
TaglineThe World's First Blackwell AI Supercomputer.The Exascale Computer in a Single Rack.
Highlights
Key Features8x NVIDIA Blackwell GPUs — 1.4 TB total HBM3e (64 TB/s bandwidth) · 72 PFLOPS FP8 training / 144 PFLOPS FP4 inference — 3× training vs DGX H100 · 15× faster real-time LLM inference per GPU vs DGX H100 · 14.4 TB/s NVLink aggregate — 2x NVLink Switch Systems72 NVIDIA Blackwell GPUs + 36 Grace CPUs in one liquid-cooled rack · 130 TB/s NVLink Switch System — all 72 GPUs act as one massive GPU · 30× faster real-time trillion-parameter LLM inference vs NVIDIA H100 · 4× faster LLM training at scale vs NVIDIA H100
At a Glance
Brand & Model
NVIDIA DGX B200NVIDIA DGX B200
NVIDIA GB200 NVL72NVIDIA GB200 NVL72
Tagline
NVIDIA DGX B200The World's First Blackwell AI Supercomputer.
NVIDIA GB200 NVL72The Exascale Computer in a Single Rack.
Highlights
Key Features
NVIDIA DGX B2008x NVIDIA Blackwell GPUs — 1.4 TB total HBM3e (64 TB/s bandwidth) · 72 PFLOPS FP8 training / 144 PFLOPS FP4 inference — 3× training vs DGX H100 · 15× faster real-time LLM inference per GPU vs DGX H100 · 14.4 TB/s NVLink aggregate — 2x NVLink Switch Systems
NVIDIA GB200 NVL7272 NVIDIA Blackwell GPUs + 36 Grace CPUs in one liquid-cooled rack · 130 TB/s NVLink Switch System — all 72 GPUs act as one massive GPU · 30× faster real-time trillion-parameter LLM inference vs NVIDIA H100 · 4× faster LLM training at scale vs NVIDIA H100
★

Expert Analysis

AI-assisted analysis based on published specifications

The DGX B200 and GB200 NVL72 both use NVIDIA Blackwell GPUs but operate at very different scales. DGX B200 is a single 10 RU, air-cooled system: eight Blackwell GPUs with 1,440 GB of total GPU memory, two Intel Xeon Platinum 8570 processors, 14.4 TB/s of aggregate NVLink bandwidth and a maximum draw of about 14.3 kW, according to NVIDIA. It is the building block of DGX BasePOD and DGX SuperPOD.

GB200 NVL72 is a whole liquid-cooled rack: 36 Grace CPUs and 72 Blackwell GPUs in one 72-GPU NVLink domain with 130 TB/s of NVLink bandwidth, 13.4 TB of HBM3e GPU memory and 17 TB of LPDDR5X CPU memory. NVIDIA positions it for real-time trillion-parameter LLM inference, quoting 30x faster inference and 4x faster LLM training than the H100.

The deciding factor is usually the facility as much as the workload. DGX B200 goes into air-cooled data centre racks one node at a time; GB200 NVL72 needs liquid-cooling infrastructure and is planned as a complete rack. Choose DGX B200 for single-node or incrementally scaled clusters, and GB200 NVL72 when a model needs a single 72-GPU NVLink domain.

NVIDIA DGX B200
Best for: Air-cooled data centres adding Blackwell AI capacity one 8-GPU node at a time.
NVIDIA GB200 NVL72
Best for: Liquid-cooled facilities running trillion-parameter models that need a single 72-GPU NVLink domain.

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NVIDIA DGX B200
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