AWS
aws.amazon.com › amazon ec2 › instance types › g4 instances
Amazon EC2 G4 Instances — Amazon Web Services (AWS)
2 days ago - Compared to comparable instances they offer up to 45% better price performance for graphics-intensive applications. ... G4dn instances, powered by NVIDIA T4 GPUs, are the lowest cost GPU-based instances in the cloud for machine learning inference and small scale training.
AWS
aws.amazon.com › about-aws › whats-new › 2025 › 06 › pricing-usage-model-ec2-instances-nvidia-gpus
Pricing and usage model updates for Amazon EC2 instances accelerated by NVIDIA GPUs - AWS
Discover more about what's new at AWS with Pricing and usage model updates for Amazon EC2 instances accelerated by NVIDIA GPUs
TRG Datacenters
trgdatacenters.com › resource › aws-gpu-pricing
AWS GPU Pricing Explained: Costs & Optimization Guide | TRG Datacenters
April 10, 2025 - Although the pricing models are straightforward, there are several factors that can influence the prices widely. Understanding these factors is key before committing to AWS GPU services: These factors include: Instance and GPU Types. The type of instance-based GPUs you choose will significantly impact your costs. For example, NVIDIA A100 GPUs are more expensive than P2 instances equipped with NVIDIA K80 GPUs.
AWS
aws.amazon.com › amazon ec2 › instance types › g5 instances
Amazon EC2 G5 Instances | Amazon Web Services
2 days ago - G5 instances feature up to 8 NVIDIA and second generation AMD EPYC processors. They also support up to 192 vCPUs, up to 100 Gbps of network bandwidth, and up to 7.6 TB of local NVMe SSD storage. ... G5 instances deliver up to 3x higher graphics performance and up to 40% better price performance than G4dn instances. They have more ray tracing cores than any other GPU-based EC2 instance, feature 24 GB of memory per GPU, and support NVIDIA RTX technology.
AWS Marketplace
aws.amazon.com › marketplace › pp › prodview-7ikjtg3um26wq
AWS Marketplace: NVIDIA GPU-Optimized AMI
It supports NVIDIA GPUs, making it ideal for machine learning, data analytics, and rendering tasks. Users can leverage advanced security features and automatic updates, ensuring reliable performance and compliance. This AMI is perfect for developers and data scientists looking to accelerate their workflows while benefiting from the flexibility and scalability of the AWS cloud.
Vantage
handbook.vantage.sh › aws › reference › aws-gpu-instances
AWS GPU Instances | Cloud Cost Handbook - Cloud Cost Handbook
This table is generated by transform_gpus.py in GitHub, with data from the Instances codebase. For more detailed information about matching CUDA compute capability, CUDA gencode, and ML framework version for various NVIDIA architectures, please see this up-to-date resource.
Reddit
reddit.com › r/aws › cheapest nvidia gpu instance?
r/aws on Reddit: Cheapest NVIDIA GPU Instance?
September 1, 2022 -
Which AWS instance would be the cheapest that has an available NVIDIA GPU? Is it the p2.xlarge ? Cost explorer sais this one is $800/month :O
Top answer 1 of 3
5
Would it be possible for you to use spot instances? This brings down our costs substantially when paired with AWS batch.
2 of 3
4
g4dn.xlarge has a T4 and is cheaper than p2.xlarge. g4g.xlarge g5g.xlarge is cheaper still, but you'll need software that will run on ARM. GPUs are generally expensive though - the hardware is very costly, and they are very power hungry (and thus expensive to cool too)
Top answer 1 of 3
2
Hello.
The following document describes the GPU-equipped instance types that can be used with EC2.
https://docs.aws.amazon.com/dlami/latest/devguide/gpu.html
I checked the prices in the price list below, and I thought that "g4dn.xlarge" was the cheapest if you were running it on demand.
https://aws.amazon.com/ec2/pricing/on-demand/?nc1=h_ls
2 of 3
0
The g4dn is among the lowest cost GPU-based instances.
If your software supports Graviton arm64, you can explore g5g instance. It is available in Regions such as Oregon us-west-2.
AWS Marketplace
aws.amazon.com › marketplace › pp › prodview-wswmisyz3jiui
AWS Marketplace: NVIDIA GPU-Optimized AMI (ARM64)
NVIDIA accelerates innovation by eliminating the complex do-it-yourself task of building and optimizing a complete deep learning software stack tuned specifically for GPUs. ... You can now purchase comprehensive solutions tailored to use cases and industries. ... AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program.
Paperspace
paperspace.com › gpu-cloud-comparison
2023 GPU Pricing Comparison: AWS, GCP, Azure & More | Paperspace
Critics have pointed out that EC2 has very few GPU options available given the market dominance that AWS enjoys in cloud computing generally. But what AWS lacks in options and configuration speed, they make up for in pricing power and volume discount.
Amazon Web Services
aws.amazon.com › aws and nvidia
NVIDIA Collaboration for Generative AI & GPU Solutions - AWS
1 week ago - Amazon EC2 instances, powered by NVIDIA GPUs, accelerate training and inference for increasingly complex LLMs and compute-intensive generative AI applications. NVIDIA NIM and NeMo microservices, part of NVIDIA AI Enterprise in the AWS Marketplace, enables organizations to unlock the potential of generative AI and LLMs at scale.
Network World
networkworld.com › home › cloud computing › iaas › amazon web services
AWS cuts prices of some EC2 Nvidia GPU-accelerated instances | Network World
September 9, 2025 - For three-year periods, costs on P4d on the Instance Savings Plan will decrease by 25%. The Compute Savings plan is not available for the same period. P4de instances get the same reduction as P4d instances across all plans. For P5 and P5en instances, AWS has reduced prices by 44% and 25%, respectively, under the On-demand plan.
AWS re:Post
repost.aws › questions › QUudlqcS-sQRqw_pbGKW--3A › low-gpu-ram-vm-options-and-pricing
Low GPU RAM VM options and pricing | AWS re:Post
March 20, 2024 - g4ad.xlarge with GPU RAM of 8 GiB has an on demand cost of $3315.9228 annually which appears to be the cheapest GPU VM option provided by AWS from my review. Is this correct or is there a cheaper option?