The first thing that drew us to Civo was the expertise they demonstrated in selecting the right GPUs for our needs. Their knowledge made all the difference.
Matt Butcher
Chief Executive Officer, Fermyon
Reserve your NVIDIA® A100 GPU today with Civo
Be the first to access the NVIDIA A100 GPUs into your infrastructure.
Reserve your GPU todayTrusted by businesses of all sizes worldwide.
A100 GPU compute for a variety of workloads, including AI & data analytics
- A100 GPUs from just $0.69 per hour
- 40GB or 80GB HBM2e memory available
- Support for compute and Kubernetes
- Transparent pricing for predictable billing
- Supported by full ML ecosystem
- Public, private, on-prem & hybrid
Maximum GPU power at the lowest possible price
Industry-leading pricing to make AI innovation accessible to everyone
| Model | Status | From price | On-demand price |
|---|---|---|---|
| A100 40GB | In Stock now | $0.69 Per GPU/h | $1.09 Per GPU/h |
| A100 80GB | In Stock now | $1.39 Per GPU/h | $1.79 Per GPU/h |
Take an in-depth look
NVIDIA A100 GPU specifications
GPU architecture
NVIDIA Ampere architecture
GPU Memory
40GB and 80GB HBM2e
Memory bandwidth
2,039GB/s
NVIDIA Ampere Architecture-Based CUDA® cores
6,912
NVIDIA Third-Generation Tensor cores
312 TFLOPS (TF32), 624 TFLOPS (FP16, BFLOAT16)
Single-precision performance (FP32)
19.5 TFLOPS
Efficiency/Security features
NEBS Level 3, Secure Boot
Max power consumption
400W (standard configuration)
Form factor
PCIe dual-slot air-cooled or single-slot liquid-cooled
Interconnect interface
NVIDIA NVLink Bridge for 2 GPUs: 600GB/s, PCIe Gen4: 64GB/s
Ideal for
AI/LLM Inference & Training, 3D Graphics
Trusted by global businesses
For our PoC, Civo impressed us by setting up a Slack Connect channel for direct access to their SRE team. Their ledge of cloud-native tech and GPUs gave us real confidence in their support.
Oliver Pinson-Roxburgh
Chief Executive Officer, Defense.com
Unlike other industry players, Civo doesn't bury hidden charges or surprise you with complex egress fees - their pricing is straightforward, and that makes all the difference for businesses trying to scale efficiently.
James Faure
Chief Executive Officer, Clairo.ai
With Civo, deployment speeds and efficiency have significantly improved. Their GPU expertise has been invaluable, boosting our service delivery and enhancing client conversion and retention.
Anuraag Gutgutia
Co-Founder, True Foundry
Discover Civo's AI/ML learning resources
Secure your GPU today
H100 Frequently Asked Questions
To reserve the NVIDIA A100 GPU, simply complete our form with your requirements and use case. Our team will then contact you to discuss the next steps and address any questions you may have.
Absolutely! Let us know you’d like a demo when you fill out our form, and we’ll arrange a session to showcase the A100’s capabilities in your specific AI or ML workflow.
Civo offers flexible pricing for NVIDIA A100 GPUs, with options for both on-demand and committed usage pricing.
For the A100 40GB, pricing starts at $0.69 per GPU/hour with a 36 month commitment, while the on-demand rate is $1.09 per GPU/hour.
For the A100 80GB, the 36 month commitment pricing starts at $1.39 per GPU/hour, and the on-demand rate is $1.79 per GPU/hour.
Larger configurations include additional CPU, RAM, and storage, with pricing scaling accordingly. To explore the full cost breakdown and find the best option for your workload, visit our pricing page here.
The NVIDIA A100 is designed for high-performance computing (HPC), AI/ML model training, deep learning inference, and data analytics. It excels in tasks such as large-scale neural network training, scientific simulations, and big data processing. If you're working with TensorFlow, PyTorch, JAX, or RAPIDS, the A100 offers significant performance improvements.
Civo’s NVIDIA A100 GPUs are available in select data centers. To check the latest availability in your preferred region, review our Region availability documentation.
Yes, you can scale up your configuration to a larger GPU instance if your workload demands more power. However, upgrading requires launching a new instance, so we recommend planning your workload scalability in advance.
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