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TATC

Advanced Computing for Southeast Asia

9/11 Moo 12, Khlong Song, Khlong Luang District, Pathum Thani 12120, Thailand
info@tatc.cloud

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  1. Services
  2. /Next-generation GPUs
  3. /NVIDIA HGX B300
NVIDIA
Roadmap

NVIDIA HGX B300

Eight-GPU Blackwell Ultra platform with 2.1TB HBM3E for AI reasoning, training and inference

NVIDIA BLACKWELL ULTRA

Specifications (manufacturer data)

NVIDIA HGX B300 integrates eight Blackwell Ultra GPUs with 2.1TB of HBM3E memory for AI reasoning, large-scale model training, agentic systems, high-throughput inference and real-time video generation.

Figures marked TBC / est. are preliminary manufacturer specifications and remain subject to confirmation. Roadmap status and manufacturer specifications do not represent available capacity or a committed delivery date.

Discuss this GPUBrowse GPUs available for enquiry
Architecture
Blackwell Ultra
VRAM per card
270GB HBM3E
Memory bandwidth
7.7 TB/s per GPU
FP16 / BF16 tensor
4.5 PFLOPS per GPU (sparse; dense 2.25 PFLOPS)
FP8 tensor
9 PFLOPS per GPU (sparse; dense 4.5 PFLOPS)
FP4 tensor
18 / 14 PFLOPS per GPU (sparse / dense)
TDP
Up to 1,100W per GPU (configurable)
Interconnect
5th-gen NVLink · 1.8 TB/s per GPU

Why it matters

  • Eight Blackwell Ultra GPUs with 2.1TB total HBM3E memory
  • 144 / 108 PFLOPS total FP4 Tensor Core compute (sparse / dense)
  • 62 TB/s total memory bandwidth and 14.4 TB/s NVLink Switch bandwidth

Built for

  • Frontier LLM training (100B+ parameters)
  • Ultra-long-context inference
  • Large MoE serving at scale

Software stack

CUDA 12.9+
PyTorch
Triton
vLLM
TensorRT-LLM
Compare accelerators

AMD MI350 Series — AMD Instinct MI355X

AMD MI350 Series

AMD Instinct MI355X

288GB HBM3E accelerator with fourth-generation AMD CDNA architecture for generative AI, training, inference and HPC

Memory
288GB HBM3E
Bandwidth
8 TB/s
TDP
1400W maximum TBP
View details
Configurations for enquiry

Reference NVIDIA configurations

Discuss the selected GPU, quantity, node design, deployment location and commercial terms with our team.

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