B200 GPU Rental

From $2.25/hr - Next-Gen Blackwell GPU for Trillion-Parameter Models

The NVIDIA B200 Tensor Core GPU represents the next generation of AI computing with the revolutionary Blackwell architecture. Featuring 192GB of HBM3e memory and up to 2.5x performance improvement over H100, the B200 is purpose-built for training and serving trillion-parameter foundation models. Experience cutting-edge AI capabilities with second-generation Transformer Engine and advanced FP4 precision support on Spheron's infrastructure.

Technical Specifications

GPU Architecture
NVIDIA Blackwell
VRAM
192 GB HBM3e
Memory Bandwidth
8.0 TB/s
Tensor Cores
5th Generation
CUDA Cores
20,480
FP64 Performance
45 TFLOPS
FP32 Performance
90 TFLOPS
TF32 Performance
2,250 TFLOPS
FP8 Performance
4,500 TFLOPS
FP4 Performance
9,000 TFLOPS
System RAM
184 GB DDR5
vCPUs
32 vCPUs
Storage
250 GB NVMe Gen5
Network
NVLink 1.8TB/s
TDP
1000W

Ideal Use Cases

🌐

Trillion-Parameter Model Training

Train the next generation of foundation models with unprecedented scale, leveraging 192GB memory and 2nd-gen Transformer Engine.

  • GPT-4 scale models with 1T+ parameters
  • Multi-modal foundation models (text, image, video, audio)
  • Scientific foundation models for drug discovery
  • Mixture-of-Experts (MoE) architectures at scale
💬

Advanced LLM Inference

Deploy ultra-large language models for production inference with industry-leading throughput and lowest cost per token.

  • Real-time inference for 100B+ parameter LLMs
  • Multi-turn conversational AI with long context
  • Retrieval-augmented generation (RAG) at scale
  • Agent-based AI systems with reasoning capabilities

Generative AI at Scale

Power next-generation generative AI applications with support for advanced diffusion models and multi-modal generation.

  • High-resolution video generation (4K/8K)
  • Real-time 3D asset generation and rendering
  • Music and audio synthesis models
  • Code generation for enterprise applications
🔬

AI Research & Innovation

Push the boundaries of AI research with cutting-edge hardware designed for experimental architectures and novel approaches.

  • Novel neural architecture development
  • Multi-agent reinforcement learning at scale
  • Quantum machine learning simulations
  • Brain-scale neural network simulation

Pricing Comparison

ProviderPrice/hrSavings
SpheronBest Value
$2.25/hr-
CoreWeave
$6.50/hr2.9x more expensive
Lambda Labs
$7.99/hr3.6x more expensive
Azure
$12.50/hr5.6x more expensive
AWS
$13.00/hr5.8x more expensive
Google Cloud
$18.75/hr8.3x more expensive

Performance Benchmarks

LLM Training (GPT-4 scale)
2.5x faster
vs H100
FP8 Inference Throughput
2.2x faster
vs H100
Multi-Modal Training
3.0x faster
vs H100
Diffusion Model Training
2.8x faster
vs H100
Memory Bandwidth
2.4x higher
vs H100
Energy Efficiency
1.8x better
vs H100

Advanced Networking for Multi-GPU Clusters

B200 features next-generation NVLink with 1.8TB/s bandwidth, enabling unprecedented GPU-to-GPU communication for massive-scale training workloads.

1.8 TB/s NVLink bandwidth per GPU
Support for up to 576 GPUs in a single cluster
5th generation NVSwitch for optimal topology
GPUDirect RDMA with 200 Gbps InfiniBand
Optimized for NCCL 2.20+ collective operations
Sub-500ns GPU-to-GPU latency
Advanced load balancing and fault tolerance
Native support for distributed training frameworks

Frequently Asked Questions

What makes B200 revolutionary compared to H100?

B200 delivers 2.5x better training performance with 2.4x more memory (192GB vs 80GB) and 2.4x higher bandwidth (8.0 TB/s vs 3.35 TB/s). The new Blackwell architecture introduces 5th-gen Tensor Cores with FP4 precision support, 2nd-gen Transformer Engine, and significantly improved energy efficiency. It's designed specifically for trillion-parameter models and next-generation AI workloads.

When should I choose B200 over H100 or H200?

Choose B200 for: training models >100B parameters, production inference of 500B+ models, multi-modal training requiring massive memory, or when pushing the boundaries of AI scale. For most production inference or models <100B parameters, H100/H200 may offer better cost-performance.

What is FP4 precision and why does it matter?

FP4 (4-bit floating point) is a new precision format in B200 that enables 2x more compute density compared to FP8. It's particularly effective for inference workloads, allowing higher throughput while maintaining model accuracy. Combined with quantization-aware training, FP4 can dramatically reduce inference costs for LLMs.

How does B200's NVLink compare to previous generations?

B200's 5th-gen NVLink provides 1.8TB/s bidirectional bandwidth, 1.8x more than H100's NVLink. This enables training of larger models across more GPUs with minimal communication overhead. The improved topology supports up to 576 GPUs in a single training cluster, essential for trillion-parameter models.

Is B200 available for immediate deployment?

B200 availability is limited as it's the newest GPU generation. Spheron is working with providers to secure B200 capacity. Contact our team to join the waitlist and discuss your requirements. We'll notify you as soon as B200 instances become available in your preferred region. Join the B200 waitlist

Ready to Get Started with B200?

Deploy your B200 GPU instance in minutes. No contracts, no commitments. Pay only for what you use.


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