What makes A100 ideal for enterprise AI?

A100 80GB offers 80GB HBM2e memory for large models, Multi-Instance GPU (MIG) for workload isolation, and 3rd gen Tensor Cores for 20x AI performance boost. It's designed for production AI workloads.

Can I run multiple workloads on A100?

Yes, A100's Multi-Instance GPU (MIG) technology allows you to partition a single A100 into up to 7 isolated GPU instances, each with dedicated memory and compute resources.

What's the difference between A100 and H100?

H100 is 6x faster than A100 for LLM training with HBM3 memory and 4th gen Tensor Cores. A100 at $3.76/hour offers better value for many workloads, while H100 at $6.62/hour provides cutting-edge performance.

VOLTAGEGPU

8x NVIDIA A100 80GB GPU Instance

The gold standard for AI training and inference. Deploy enterprise-grade GPU compute in seconds.

Starting at

$2.31/hour

Deploy Time

30-60 sec

Regions

Decentralized — location varies (active nodes)

Availability

Depends on availability on Bittensor

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8x NVIDIA A100-SXM4-80GB

High Performance

$6.02/hour

CPU

126 cores Intel(R) Xeon(R) Platinum 8462Y+

Memory

787 GB

Disk

24,636 GB

Network

↑1115 / ↓1204 Mbps

Location

Des Moines, United States

Uptime

23 days 20 hrs 20 mins

Estimated monthly cost:$4,334

Technical Specifications

GPU Performance

6,912 CUDA Cores
432 Tensor Cores (3rd Gen)
19.5 TFLOPS FP32
312 TFLOPS Tensor

Memory

80GB HBM2e
1,555 GB/s Bandwidth
40MB L2 Cache
ECC Support

Connectivity

NVLink 3.0 (600 GB/s)
PCIe Gen 4.0
Multi-Instance GPU (MIG)
GPUDirect RDMA

AI Features

Structural Sparsity
Multi-Instance GPU
TF32 Precision
BF16 Support

Ideal Use Cases

Large Language Models

Train and fine-tune LLMs like GPT, LLaMA, and custom models with 80GB memory capacity.

GPT-3 fine-tuning
LLaMA 70B inference
Custom transformer models

Scientific Computing

Accelerate HPC workloads with double precision performance and massive memory bandwidth.

Molecular dynamics
Climate modeling
Computational fluid dynamics

AI Training at Scale

Distributed training with NVLink for maximum throughput and efficiency.

Computer vision models
Recommendation systems
Reinforcement learning

Performance Comparison

Specification	A100 80GB	A100 40GB	V100 32GB
Memory	80 GB HBM2e	40 GB HBM2	32 GB HBM2
Memory Bandwidth	1,555 GB/s	1,555 GB/s	900 GB/s
FP32 Performance	19.5 TFLOPS	19.5 TFLOPS	15.7 TFLOPS
Tensor Performance	312 TFLOPS	312 TFLOPS	125 TFLOPS
NVLink	600 GB/s	600 GB/s	300 GB/s
Price/Hour	From $2.31	From $1.89	From $1.14

Frequently Asked Questions

What is the difference between A100 40GB and 80GB versions?

The A100 80GB doubles the HBM2e memory capacity, allowing for larger models and datasets. It's better suited for large language models and extensive batch processing.

Can I use multiple A100 GPUs together?

Yes, our A100 instances support multi-GPU configurations with NVLink interconnect at 600 GB/s bandwidth. You can scale up to 8x A100 in a single node for distributed training.

What frameworks are pre-installed?

Our A100 instances come with CUDA 11.8+, PyTorch 2.0+, TensorFlow 2.13+, JAX, and other popular ML frameworks pre-installed. Custom Docker images are also supported.

Is there a minimum billing period?

Billing is per hour with a minimum of 1 hour. After the first hour, billing is prorated to the minute. No long-term commitments required.

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