NVIDIA A100 GPU Rental - Instant Access | $1.79/hr | No Waitlist
✓ Up to $300K in Credits Available

NVIDIA A100
GPUs Ready to Deploy

Best price-performance for fine-tuning and inference. Deploy across AWS, Azure, GCP with emma credits—instant provisioning, no lock-in.

Backed by
RTP GlobalSmartfinDeep.vcAltaIRCircleRock

Why Run A100 on emma

Multi-cloud GPU platform with up to $100K initial credits (scale to $300K)

No Long-Term Contracts

Pay-as-you-go hourly billing. Scale up for production, scale down after launch. No annual commits, no minimum spend requirements.

PoC to Production in Days

Start with A100 credits today, deploy production workloads this week. Unified control plane means your PoC setup IS your production setup.

Multi-Cloud Execution Layer

emma isn't just a GPU vendor—it's your infrastructure platform. Deploy A100 on AWS today, H100 on GCP tomorrow, same tooling and billing.

Seamless GPU Upgrades

Start A100 at $1.79/hr, upgrade to H100 when you need it. Zero migration, zero replatforming. Your code runs everywhere.

Unified Control Plane

One dashboard for all clouds and GPUs. Manage A100, H100, H200 across AWS, Azure, GCP from a single interface.

$300K in Cloud Credits

Up to $100K initial allocation + $200K top performer bonus. Use on any GPU, any cloud. Credits scale with your business.

NVIDIA A100 80GB

Best price-performance for fine-tuning & inference • Multi-cloud

$1.79
per hour on-demand
Available
Cheaper than: H100 ($2.79) | H200 ($3.29)
More capable than: L40S ($1.49) for training
GPU Memory
80 GB HBM2e
Memory Bandwidth
2 TB/s
FP32 Performance
19.5 TFLOPS
Tensor Performance
312 TFLOPS
NVLink
600 GB/s
Multi-Instance GPU
7 instances

Perfect for Your AI Workloads

Production-ready infrastructure for demanding AI applications

LLM Fine-tuning up to 70B

Fine-tune Llama 2 70B with QLoRA in under 24 hours. 80GB HBM2e handles 4K+ context with room for optimizer states. Multi-GPU clusters available with NVLink.

High-Throughput Inference

Deploy production inference endpoints with sub-100ms latency. Batch processing for computer vision, NLP tasks, and real-time recommendation systems at scale.

Computer Vision Training

Train ResNet, EfficientNet, YOLO, and transformer-based vision models. Handle high-resolution imagery and video processing with ease. Ideal for object detection and segmentation.

Research & Development

Experiment with cutting-edge architectures, run hyperparameter sweeps, and prototype new models. Full Jupyter, PyTorch, and TensorFlow support out of the box.

Data Processing & Analytics

Accelerate data preprocessing, feature engineering, and ETL pipelines with RAPIDS. GPU-accelerated analytics for massive datasets with cuDF and cuML.

Reinforcement Learning

Train RL agents for gaming, robotics, and autonomous systems. High memory enables complex environment simulations and large replay buffers.

Ready to run your AI workloads on A100?

Get Started with Credits →

Enterprise Features Included

Production-grade infrastructure without the premium pricing

Instant Deployment

Provision A100 instances in under 60 seconds. No waiting lists, no queues. Start training immediately.

Dedicated Hardware

True bare-metal A100 access with no noisy neighbors. Your workloads get 100% of GPU resources.

Multi-GPU Clusters

8-GPU training nodes with NVLink connectivity. Scale from single GPUs to massive clusters for distributed training.

Global Availability

Low latency access from US, EU, and APAC. Edge deployments supported.

Auto-Scaling

Scale from 1 to 100+ A100 GPUs on demand. Automatic scaling based on workload requirements.

99.9% Uptime SLA

Enterprise-grade reliability with financial-backed SLA. 24/7 monitoring and support included.

Built for Teams with Real Compute Needs

We work best with teams that are ready to ship, not just explore

GPU or AI/ML workloads Training, inference, batch processing, or HPC
$5K+/month cloud spend Current or projected within 6 months
Ready to migrate in 30 days Not "exploring options" — ready to ship
Open to case study Share your success (anonymized if needed)

Get Started with A100 Credits

Response time SLA: under 5 hours

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What Happens Next

From application to GPUs in days

1

Review

Within 5 hours

2

Architecture call

15 minutes

3

Onboarding

Platform setup

4

Credits live

Start deploying

Credits are usage-based billing credits, not cash. No minimum spend, no forced commitment. Use on A100, H100, H200, or any GPU across AWS, Azure, GCP.