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Why the B300 Changes Everything

288GB

HBM3e Memory Per GPU

8TB/s

Memory Bandwidth

15 PFLOPS

Dense FP4 (per GPU)

1.5×

vs. B200 NVL72

Why Choose NVIDIA B300 AI Servers from Cyfuture AI?

Unmatched Memory Density for Frontier Models

The NVIDIA B300 GPU ships with 288GB of HBM3e memory — built using 12-high HBM stacks instead of the B200's 8-high configuration. That's 50% more capacity than the B200 and nearly 2× the H200. For AI teams running 200B+ parameter models, MoE architectures, or 1M+ token long-context workloads, this isn't an incremental upgrade — it's the difference between fitting a full model on a single GPU or having to shard it across multiple nodes, adding latency and coordination overhead.

Inference-Optimized Blackwell Ultra Architecture

The B300 AI GPU's 5th-generation Tensor Cores introduce native FP4 (NVFP4) support through the second-generation Transformer Engine. FP4 precision enables 2× the throughput of FP8 for inference workloads without meaningful accuracy loss on modern LLMs. Combined with a dual-reticle design linked by a 10TB/s on-package interface and 160 Streaming Multiprocessors across 8 GPCs, the B300 is purpose-built for the steady-state inference economics that define production AI deployments.

NVLink 5 Ultra — 1.8TB/s GPU-to-GPU Bandwidth

Each B300 GPU AI server ships with NVLink 5 Ultra, delivering 1.8TB/s bidirectional bandwidth per GPU. In GB300 NVL72 rack-scale configurations, 72 B300 GPUs are connected via NVSwitch 3.0 into a unified 20TB+ memory domain — enabling near-linear scaling for distributed training of trillion-parameter models with minimal inter-GPU communication overhead.

Enterprise-Grade B300 GPU Infrastructure

Cyfuture AI's B300 GPU Server deployments run on purpose-built infrastructure with direct liquid cooling (mandatory at 1,400W TDP), 800Gbps ConnectX-8 SuperNIC networking, Gen5 NVMe storage, and redundant power architecture. Every node is pre-configured, tested, and supported by 24×7 enterprise technical assistance — so your team focuses on models, not maintenance.

Transparent NVIDIA B300 GPU Pricing

Cyfuture AI offers competitive, performance-based NVIDIA B300 GPU price tiers for both short-commitment and dedicated deployments. No hidden infrastructure surcharges. No surprise billing. Transparent pricing tied to actual GPU-hours consumed — whether you're provisioning a single B300 AI GPU or scaling to a multi-node cluster.

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Servers Now

Access 288GB per-GPU memory at 8TB/s bandwidth. The highest-VRAM single GPU available today — built for the workloads that matter most.

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Technical Specifications
NVIDIA B300 GPU — Core Specifications

Feature Specification
Architecture NVIDIA Blackwell Ultra (dual-reticle, 208B transistors)
GPU Memory 288GB HBM3e per GPU (12-high HBM stacks)
Memory Bandwidth 8TB/s (per GPU)
Streaming Multiprocessors 160 SMs across 8 GPCs
CUDA Cores 20,480 per GPU
Tensor Cores 5th Generation — FP4, FP8, FP16, BF16, INT8 native
Dense FP4 Throughput 15 PFLOPS per GPU (13 PFLOPS full implementation)
NVLink Interconnect NVLink 5 Ultra — 1.8TB/s bidirectional per GPU
On-Package Interface 10TB/s dual-die bridge
PCIe Generation Gen6
Form Factor SXM (HGX B300 baseboard, GB300 NVL72 rack)
TDP 1,400W (liquid cooling required)
FP4 vs B200 ~1.5× dense FP4 uplift
Attention Performance vs B200 2× improvement
Software Stack CUDA 12+, TensorRT-LLM, vLLM, NIM, RAPIDS, PyTorch, JAX

NVIDIA B300 AI Server
— System Configuration

Component Specification
Base Platform HGX B300 8-GPU or GB300 NVL72 Rack System
GPUs per Node 8× NVIDIA B300 (HGX) or 72× B300 (NVL72 rack)
Total GPU Memory (8-GPU node) 2.3TB HBM3e
Total GPU Memory (NVL72) 20.7TB unified HBM3e (NVSwitch fabric)
Networking 800G ConnectX-8 SuperNICs (OSFP) per node
GPU Interconnect NVSwitch 3.0 — 900GB/s × 18-port fabric
NVMe Storage 8× 7.68TB Gen5 NVMe (61.44TB total per node)
Cooling Direct Liquid Cooling (DLC) — mandatory
Power per Node ~11.2kW (8× B300 at 1,400W)
Management NVIDIA DGX OS / Cisco Intersight (partner configs)
OS / Software Ubuntu Server LTS, CUDA 12+, NVIDIA AI Enterprise

NVIDIA B300
GPU Server — Hardware Configuration

Part Number Description / Qty / Notes
HGX-B300-8G NVIDIA HGX B300 8-GPU Baseboard — 8× B300 GPUs, NVSwitch fabric
CAB-C19-C20-IND Power Cord C19-C20 India — Qty: 8
NVL-B300-72 GB300 NVL72 Rack Config — 72× B300 GPUs, NVLink 5 mesh, liquid cooling
CX8-800G-QSFP ConnectX-8 SuperNIC — 2× 800G OSFP ports for GPU-to-GPU InfiniBand
NVS-B300-36 NVSwitch 3.0 Module — 900GB/s × 18-port, rack-level GPU fabric
SSD-7T68-GEN5 7.68TB Gen5 NVMe U.2 Drive — Qty: 8 (61TB total NVMe pool)
DC-MGT-SAAS Cisco Intersight SaaS — Management Platform
DC-MGT-IS-SAAS-ES Infrastructure Services SaaS/CVA — Essentials
CON-L1NCD-B300 3-Year 24×7 TAC — Next Calendar Day Hardware Support

Key Hardware Features

01

Memory & Compute

• 288GB HBM3e Per GPU: 12-high memory stacks eliminate model sharding for 200B–400B+ parameter LLMs, keeping full weights, KV-cache, and activations in-GPU.

• 15 PFLOPS FP4 Per GPU: Native NVFP4 Tensor Core support via the 2nd-gen Transformer Engine — maximum inference throughput with minimal accuracy degradation.

• Dual-Reticle Design: Two dies connected by a 10TB/s on-package bridge deliver the compute density of a monolithic design at scale.

02

Interconnect & Networking

• NVLink 5 Ultra — 1.8TB/s Bidirectional: The fastest GPU-to-GPU interconnect available. Sustains distributed training across nodes without InfiniBand bottlenecks.

• NVSwitch 3.0 Fabric: 72-GPU all-to-all connectivity in GB300 NVL72 racks, creating a unified 20TB+ addressable memory domain.

• 800G ConnectX-8 SuperNICs: OSFP-based NICs purpose-built for Blackwell Ultra — mandatory for full rack-to-rack bandwidth at Blackwell speeds.

03

Cooling & Power

• Direct Liquid Cooling (Mandatory): Blackwell Ultra's 1,400W TDP necessitates DLC — capturing up to 98% of thermal output with zero performance throttling.

• AC and DC Power Options: DGX B300 supports both AC and DC power delivery, enabling deployment in NVIDIA MGX racks and traditional enterprise data center environments.

• Redundant PSU Architecture: Hot-swappable power supplies with balanced load distribution across 8 power cords per node.

04

Management & Support

• NVIDIA DGX OS / NVIDIA AI Enterprise: Full-stack software for model deployment, monitoring, and orchestration — pre-integrated.

• Cisco Intersight (Partner Configs): -based infrastructure management with real-time telemetry, alerting, and remote remediation.

• 24×7 TAC + Next Calendar Day Hardware: Cyfuture AI ensures consistent uptime with round-the-clock support and rapid on-site hardware replacement.

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.

Power Your AI Factory
with B300 GPU Server

Set up distributed inference or training across B300 AI GPU nodes with 800Gbps ConnectX-8 SuperNICs, NVSwitch 3.0 fabric, and direct liquid cooling — fully managed by Cyfuture AI.

Get Started with NVIDIA B300 AI Server
H200 GPUs

Real-World Applications of the NVIDIA B300 GPU

Frontier LLM Inference & Agentic AI

The B300 GPU AI server was designed from the ground up for inference — the steady-state workload that dominates production AI economics. With 288GB of HBM3e, teams can serve 405B+ parameter models on a single node without tensor-parallel splits, dramatically reducing latency. For agentic systems running multi-step reasoning chains, the enlarged KV-cache headroom means longer context windows (1M+ tokens) without eviction.

Trillion-Parameter Model Training

In GB300 NVL72 configurations, 72 B300 GPUs share a 20TB+ unified memory domain via NVSwitch. This enables end-to-end training of trillion-parameter models — including Mixture-of-Experts architectures — that exceed the addressable memory of any individual node. NVLink 5's 1.8TB/s per-GPU bandwidth sustains near-linear scaling across the full rack.

Generative AI — Text, Image, Video, Code

Buy NVIDIA B300 AI Server capacity for next-generation generative AI pipelines. The FP4 Transformer Engine delivers 2× the attention throughput of previous Blackwell generations, making real-time multimodal generation — across text, image, video, and code — commercially viable at enterprise scale.

Long-Context RAG & Mixture-of-Experts

RAG systems with million-token context windows and sparse MoE models with hundreds of experts place extreme pressure on GPU memory. The B300's 288GB HBM3e absorbs large retrieval corpora and expert weights simultaneously, eliminating the need for complex memory offloading schemes that degrade throughput.

High-Performance Scientific Computing

While optimized for AI inference, the B300 AI GPU supports high-throughput FP16 and BF16 workloads relevant to molecular dynamics, drug discovery, climate simulation, and computational fluid dynamics. For FP64-heavy HPC workloads, the H200 remains the stronger choice — the B300 is inference-weighted and delivers near-zero FP64 throughput by design.

Computer Vision & Autonomous Systems

Deploy advanced vision transformers (ViTs), diffusion models, and multi-modal perception stacks on B300 GPU Server infrastructure. The memory headroom accommodates large model ensembles for autonomous vehicle training pipelines, industrial inspection, and satellite imagery analysis without multi-GPU model parallelism overhead.

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NVIDIA B300 GPU Server

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 B300 AI Server is purpose-built for inference at scale. With 288GB of HBM3e memory per GPU and 8TB/s bandwidth, it can hold entire 405B+ parameter models — including KV-cache — on a single GPU, eliminating inter-node communication overhead. Its 5th-generation Tensor Cores with native FP4 support deliver 15 PFLOPS dense compute per GPU, enabling ultra-low latency at high throughput.

The NVIDIA B300 GPU is the successor to the B200 within the Blackwell Ultra generation. It offers 288GB of HBM3e vs. 192GB in the B200 (50% more) and 141GB in the H200. Memory bandwidth jumps to 8TB/s from 4.8TB/s on the H200. Dense FP4 throughput increases ~33% over the B200. The B300 is optimized for inference-heavy deployments where memory capacity and bandwidth dominate performance.

Yes. Cyfuture AI supports multi-node B300 AI GPU cluster configurations. Each GPU ships with NVLink 5 Ultra providing 1.8TB/s bidirectional bandwidth for GPU-to-GPU communication. In GB300 NVL72 rack configurations, 72 B300 GPUs form a unified 20TB+ memory domain over NVSwitch fabric, enabling near-linear scaling for trillion-parameter model training.

The B300 operates at 1,400W TDP, requiring direct liquid cooling (DLC). Cyfuture AI's data centers are equipped with liquid cooling infrastructure capable of handling Blackwell Ultra-class power densities. Our facilities deliver the appropriate power, cooling, and network topology — you don't need to worry about the infrastructure layer.

The B300 AI GPU supports PyTorch, TensorFlow, JAX, NVIDIA CUDA 12+, TensorRT-LLM, vLLM, RAPIDS, and NVIDIA AI Enterprise. The Transformer Engine with FP4 Tensor Core acceleration is natively supported, enabling the highest inference throughput for LLMs. NVIDIA NIM microservices can also be deployed for optimized model serving.

Every B300 GPU Infrastructure deployment from Cyfuture AI includes: pre-configured B300 hardware, enterprise-grade NVLink/NVSwitch networking, 800G ConnectX-8 SuperNICs, Gen5 NVMe storage, liquid cooling, 24×7 technical support, and management software. Turnkey deployment is standard — from procurement to operational readiness.

Cyfuture AI offers transparent, competitive NVIDIA B300 GPU price tiers for both short-term and committed deployments. Pricing is performance-based with no hidden infrastructure fees. Contact our sales team for a customized B300 GPU Server quote aligned to your workload requirements and cluster size.

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Access enterprise-grade NVIDIA B300 GPU infrastructure designed for AI training, inference, multimodal
applications, and next-generation reasoning models.

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