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 Answer from Riku_Kobayashi on repost.aws
Vantage
instances.vantage.sh › aws › ec2 › g4dn.xlarge
g4dn.xlarge pricing and specs - Vantage
The g4dn.xlarge instance is in the GPU instance family with 4 vCPUs, 16 GiB of memory and up to 25 Gibps of bandwidth starting at $0.526 per hour.
AWS
aws.amazon.com › amazon ec2 › pricing › on-demand pricing
EC2 On-Demand Instance Pricing
6 days ago - On-Demand Instances let you pay for compute capacity by the hour or second (minimum of 60 seconds) with no long-term commitments. This frees you from the costs and complexities of planning, purchasing, and maintaining hardware and transforms what are commonly large fixed costs into much smaller ...
AWS
aws.amazon.com › amazon ec2 › instance types › g4 instances
Amazon EC2 G4 Instances — Amazon Web Services (AWS)
6 days ago - G4dn instances, powered by NVIDIA T4 GPUs, are the lowest cost GPU-based instances in the cloud for machine learning inference and small scale training. They also provide high performance and are a cost-effective solution for graphics applications that are optimized for NVIDIA GPUs using NVIDIA libraries such as CUDA, CuDNN, and NVENC.
Suggest instance type NVIDIA GPU has the best cost
My system is using the EC2 g4dn.xlarge instance type to run stable diffusion or train lora. Currently I want to find an NVIDIA GPU type version that costs less than g4dn.xlarge. Lower configuration... More on repost.aws
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August 9, 2024Benchmarking Inexpensive AWS Instances
Here's the data formatted in table for easier viewing: AWS Instances Instance Type | Cores | RAM | GPU | Prompt Eval Rate (tokens/s) | Eval Rate (tokens/s) | Price ($/hr) | Price ($/mo) | c7g.8xlarge | 32 | 64GB | - | 38.38 | 25.07 | 1.27 | 941.16 | r6g.4xlarge | 16 | 128GB | - | 10.15 | 8.29 | 0.88 | 657.10 | g4dn.xlarge | 4 | 16GB | 16GB | 222.23 | 41.71 | 0.58 | 434.50 | g4dn.2xlarge | 8 | 32GB | 32GB | 214.25 | 41.74 | 0.84 | 621.24 | g5.xlarge | 4 | 16GB | 24GB | 624.29 | 68.08 | 1.12 | 831.05 | g5.2xlarge | 8 | 32GB | 24GB | 624.48 | 66.67 | 1.35 | 1,000.96 Vs Local Machines Machine Type | Cores | RAM | GPU | Prompt Eval Rate (tokens/s) | Eval Rate (tokens/s) | M2 MacMini | - | 8GB | <8GB | 66.38 | 18.33 | M1 MacBook Air | - | 16GB | <16GB | 71.58 | 11.46 | Home PC w/RTX 3080 | - | 64GB | 10GB | 185.67 | 83.79 More on reddit.com
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June 10, 2024AWS (g4dn.xlarge) for gaming
I've been using g4dn.xlarge for cloud gaming for a while and it works well, even though the server is not close to me. Made a video about it here More on reddit.com
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December 3, 2020amazon web services - Which is lower cost, Sagemaker or EC2? - Stack Overflow
For example, ml.p2.8xlarge for training job at ap-northeast on Sagemaker takes 16.408 USD / hour, but p2.8xlarge for on-demand at ap-northeast on Ec2 takes 12.336 USD/hour. Is it cheap to just trai... More on stackoverflow.com
EC2 Pricing Calculator
costcalc.cloudoptimo.com › aws-pricing-calculator › ec2 › g4dn.xlarge
g4dn.xlarge Pricing and Specs: AWS EC2
Explore the EC2 g4dn.xlarge instance type and its costs across various regions, empowering you to make informed decisions for your cloud deployment strategy.
Bigbell
bigbell.ai › coin › aws › ec2 › g4dn.xlarge
g4dn.xlarge pricing and specs - BigBell
The g4dn.xlarge instance is in the gpu instance family with 4 vCPUs, 16.0 GiB of memory and up to 25 Gibps of bandwidth starting at $0.526 per hour.
Cloudzero
advisor.cloudzero.com › aws › ec2 › g4dn.xlarge
g4dn.xlarge Instance Specs And Pricing
CloudZero's intelligent platform helps you optimize cloud costs and improve infrastructure efficiency.
Economize
economize.cloud › resources › aws › pricing › ec2 › g4dn.12xlarge
g4dn.12xlarge pricing: $2855.76 monthly - AWS EC2
The g4dn.12xlarge instance is in the g4dn family with 48 vCPUs and 192 GiB of memory, priced from $3.91/hr or $2855.76/mo.
Top answer 1 of 3
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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
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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.
CloudPrice
cloudprice.net › amazon web services › ec2 › g4dn.xlarge
g4dn.xlarge specs and pricing | AWS | CloudPrice
October 24, 2025 - Amazon EC2 instance g4dn.xlarge with 4 vCPUs, 16 GiB RAM and 1 x NVIDIA T4 16 GiB. Available in 23 regions starting from $383.98 per month.
Reddit
reddit.com › r/localllama › benchmarking inexpensive aws instances
r/LocalLLaMA on Reddit: Benchmarking Inexpensive AWS Instances
June 10, 2024 -
I recently did some testing using Dolphin-Llama3 across various (inexpensive-ish) AWS instances to compare performance. The results are in line with what one might expect.
Testing was done using default settings with Ollama. I spun up a new instance on Ubuntu, installed Ollama and ran it with Dolphin-Llama3 —verbose.
Key Takeaways:
-Fastest Prompt Eval Rate: AWS g5 (fastest AWS instance tested)
-Fastest Eval Rate: Home PC w/RTX 3080
-Best Cost-Performance Balance: AWS g4dn.xlarge offers a good balance of performance and cost, at $0.58/hr.
-GPU speed is the key differentiator. Within the same family of models, such as the g4dn and g5 instances, the evaluation rates remain consistent. If the model fits in GPU memory there is no need for more cores/memory.
-I did notice that the more system memory available the greater number of tokens used in the output.
Test Results
AWS Instances
c7g.8xlarge (Compute Instance) •32 cores, 64GB RAM •Prompt Eval Rate: 38.38 tokens/s •Eval Rate: 25.07 tokens/s •Price: $1.27/hr, $941.16/mo r6g.4xlarge (Memory Instance) •16 cores, 128GB RAM •Prompt Eval Rate: 10.15 tokens/s •Eval Rate: 8.29 tokens/s •Price: $0.88/hr, $657.10/mo g4dn.xlarge (GPU Instance) •4 cores, 16GB RAM, 16GB GPU •Prompt Eval Rate: 222.23 tokens/s •Eval Rate: 41.71 tokens/s •Price: $0.58/hr, $434.50/mo g4dn.2xlarge (GPU Instance) •8 cores, 32GB RAM, 32GB GPU •Prompt Eval Rate: 214.25 tokens/s •Eval Rate: 41.74 tokens/s •Price: $0.84/hr, $621.24/mo g5.xlarge (GPU Instance) •4 cores, 16GB RAM, 24GB GPU •Prompt Eval Rate: 624.29 tokens/s •Eval Rate: 68.08 tokens/s •Price: $1.12/hr, $831.05/mo g5.2xlarge (GPU Instance) •8 cores, 32GB RAM, 24GB GPU •Prompt Eval Rate: 624.48 tokens/s •Eval Rate: 66.67 tokens/s •Price: $1.35/hr, $1,000.96/mo
Local Machines
M2 MacMini •M2, 8GB RAM, <8GB GPU •Prompt Eval Rate: 66.38 tokens/s •Eval Rate: 18.33 tokens/s M1 MacBook Air •M1, 16GB RAM, <16GB GPU •Prompt Eval Rate: 71.58 tokens/s •Eval Rate: 11.46 tokens/s Home PC w/RTX 3080 •Intel i5, 64GB RAM, 10GB GPU •Prompt Eval Rate: 185.67 tokens/s •Eval Rate: 83.79 tokens/s
Oracle Ampere
Ampere 16 Core, 32GB RAM •Prompt Eval Rate: 11.96 tokens/s (Duration: 1m34.955180835s) •Eval Rate: 9.01 tokens/s (Duration: 1m28.461256s) •Price: $0.1276/hr, $95/mo Ampere 32 Core, 32GB RAM •Prompt Eval Rate: 22.54 tokens/s (Duration: 47.93207936s) •Eval Rate: 14.11 tokens/s (Duration: 44.423782s) •Price: $0.2796/hr, $208/mo
Here's the data formatted in table for easier viewing - courtesy of u/sergeant113. https://www.reddit.com/r/LocalLLaMA/comments/1dclmwt/comment/l7zrgzm/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button
Top answer 1 of 5
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Here's the data formatted in table for easier viewing: AWS Instances Instance Type | Cores | RAM | GPU | Prompt Eval Rate (tokens/s) | Eval Rate (tokens/s) | Price ($/hr) | Price ($/mo) | c7g.8xlarge | 32 | 64GB | - | 38.38 | 25.07 | 1.27 | 941.16 | r6g.4xlarge | 16 | 128GB | - | 10.15 | 8.29 | 0.88 | 657.10 | g4dn.xlarge | 4 | 16GB | 16GB | 222.23 | 41.71 | 0.58 | 434.50 | g4dn.2xlarge | 8 | 32GB | 32GB | 214.25 | 41.74 | 0.84 | 621.24 | g5.xlarge | 4 | 16GB | 24GB | 624.29 | 68.08 | 1.12 | 831.05 | g5.2xlarge | 8 | 32GB | 24GB | 624.48 | 66.67 | 1.35 | 1,000.96 Vs Local Machines Machine Type | Cores | RAM | GPU | Prompt Eval Rate (tokens/s) | Eval Rate (tokens/s) | M2 MacMini | - | 8GB | <8GB | 66.38 | 18.33 | M1 MacBook Air | - | 16GB | <16GB | 71.58 | 11.46 | Home PC w/RTX 3080 | - | 64GB | 10GB | 185.67 | 83.79
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I use the Hetzner 16-core 32GB ARM instances when I need something cheap and dirty. The cost is 1/10th of even the cheapest AWS setup you have here, so if you aren't worried about speed that might be the way to go.
Amazon EC2
instances.vantage.sh
Amazon EC2 Instance Comparison
A free and easy-to-use tool for comparing EC2 Instance features and prices.
Economize
economize.cloud › resources › aws › pricing › ec2 › g4dn.xlarge
g4dn.xlarge pricing: $383.98 monthly - AWS EC2
1 week ago - The g4dn.xlarge instance is in the g4dn family with 4 vCPUs and 16 GiB of memory, priced from $0.53/hr or $383.98/mo.
Umbrella
umbrellacost.com › home › learning center › aws cost management › amazon ec2 g4 instances
Using AWS EC2 G4dn and G4ad | Amazon EC2 G4 | Umbrella
April 10, 2025 - In July 2021, AWS expanded the G4ad subfamily with the g4ad.xlarge and g4ad.2xlarge sizes, which are designed to be cost-effective for workloads that don’t need the high vCPU and system memory that current larger G4ad instance sizes offer — rounding out their AMD offering and providing the lowest cost GPU instance in the AWS Cloud.
CloudPrice
cloudprice.net › amazon web services › ec2 › g4dn.2xlarge
g4dn.2xlarge specs and pricing | AWS | CloudPrice
2 weeks ago - Amazon EC2 instance g4dn.2xlarge with 8 vCPUs, 32 GiB RAM and 1 x NVIDIA T4 16 GiB. Available in 23 regions starting from $548.96 per month.
Ec2pricing
ec2pricing.net
EC2 Instance Types & Pricing
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Reddit
reddit.com › r/cloudygamer › aws (g4dn.xlarge) for gaming
r/cloudygamer on Reddit: AWS (g4dn.xlarge) for gaming
December 3, 2020 -
I want to know what are people's experiences on using Amazon AWS for gaming. There are no cloud gaming services near my country due to which latency is very big problem. The closest AWS region to me has a latency of 35ms as measured on cloudping and the prices are very cheap with spot instances ($0.35/hr for g4dn.xlarge which has Nvidia T4 GPU). So I wanna know if gaming on AWS is viable ?
Thank you
Top answer 1 of 3
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I've been using g4dn.xlarge for cloud gaming for a while and it works well, even though the server is not close to me. Made a video about it here
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Been using them for a while. However, do note that $0.35/hr only takes into account the compute time. EBS/Snapshots for save games, etc cost more. Based on my usage (I live near ap-southeast-1 and had one instance on standby most of the time), it cost me SGD15/month for a 120GB gp2. Add in network costs and other miscellaneous stuff and it nets to about SGD20/month. However, if you finish a game quickly you can delete the instance and volume, it's just mildly annoying in the sense you have to set it up again. However, NVIDIA has a nice free AMI with all the drivers pre-installed and Parsec has an easy installation script that works pretty fast. Also, consider the fact that installing games on AWS is alot faster than downloading games over WIFI - based on my experience, something like > 10x faster because AWS's network throughput is way better than whatever your telco gives you (we're not talking about latency here). As for your gaming experience, it depends on alot of other factors. I've tried competitive FPS on the system and let's just say, get rekt (I consider myself above average if I play on my own computer). If we're talking casual FPS (against AI), it's very playable :) If we're talking about using the EC2 to run a graphics intensive game that you kinda "throw away once you're done with the game", that would otherwise eat up 80GB of your hard drive space, like GTA, CyberPunk, I'd say it's a perfect use case. If you don't game much, like me, it's also great because you can just shut down whenever you stop playing for long durations and spin them back up again. Just make sure you have some kind of system to save your progress for the games that don't have cloud saves. Edit: goes without saying but, do remember to pause (i.e. STOP) your instance when you're not using it unless you're very happy paying 24 * 31 * 0.35 = $260/mth. In which case, are you sure AWS is right for you?
Top answer 1 of 5
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I've listed some pros and cons from experience...
..., as opposed to marketing materials. If I were to guess, I'd say you have a much higher chance to experience all the drawbacks of SageMaker, than any one of the benefits.
Drawbacks
- Cloud vendor lock in: free improvements in the open source projects in the future and better prices in competitor vendors are difficult to get. Why don't AWS invest developers in JupyterLab, they have done limited work in open source. Find some great points here, where people have experienced companies using as few AWS services as possible with good effect.
- SageMaker instances are currently 40% more expensive than their EC2 equivalent.
- Slow startup, it will break your workflow if every time you start the machine, it takes ~5 minutes. SageMaker Studio apparently speeds this up, but not without other issues. This is completely unacceptable when you are trying to code or run applications.
- SageMaker Studio is the first thing they show you when you enter SageMaker console. It should really be the last thing you consider.
- SageMaker Studio is more limited than SageMaker notebook instances. For example, you cannot mount an EFS drive.I spoke to a AWS solutions architect, and he confirmed this was impossible (after looking for the answer all over the internet). It is also very new, so there is almost no support on it, even by AWS developers.
- Worsens the disorganised Notebooks problem. Notebooks in a file system can be much easier to organise than using JupyterLab. With SageMaker Studio, a new volume gets created and your notebooks lives in there. What happens when you have more than 1...
- Awful/ limited terminal experience, coupled with tedious configuration (via Lifecycle configuration scripts, which require the Notebook to be turned off just to edit these scripts). Additionally, you cannot set any lifecycle configurations for Studio Notebooks.
- SageMaker endpoints are limited compared to running your own server in an EC2 instance.
- It may seem like it allows you to skip certain challenges, but in fact it provides you with more obscure challenges that no one has solved. Good luck solving them. The rigidity of SageMaker and lack of documentation means lots of workarounds and pain. This is very expensive.
Benefits
These revolve around the SageMaker SDK (the Sagemaker console and SageMaker SDK) (please comment or edit if you found any more benefits)
- Built in algorithms (which you can easily just import in your machine learning framework of choice): I would say this is worse than using open source alternatives.
- Training many models easily during hyperparameter search YouTube video by AWS (a fast way to spend money)
- Easily create machine learning related AWS mechanical turk tasks. However, mturk is very limited within SageMaker, so youre better off going to mturk yourself.
My suggestion
If you're thinking about ML on the cloud, don't use SageMaker. Spin up a VM with a prebuilt image that has PyTorch/ TensorFlow and JupyterLab and get the work done.
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You are correct about EC2 being cheaper than Sagemaker. However you have to understand their differences.
- EC2 provides you computing power
- Sagemaker (try to) provides a fully configured environment and computing power with a seamless deployment model for you to start training your model on day one
If you look at Sagemaker's overview page, it comes with Jupyter notebooks, pre-installed machine learning algorithms, optimized performance, seamless rollout to production etc.
Note that this is the same as self-hosting a EC2 MYSQL server and utilizing AWS managed RDS MYSQL. Managed services always appears to be more expensive, but if you factor in the time you have to spent maintaing server, updating packages etc., the extra 30% cost may be worth it.
So in conclusion if you rather save some money and have the time to set up your own server or environment, go for EC2. If you do not want to be bothered with these work and want to start training as soon as possible, use Sagemaker.
Cloudzero
advisor.cloudzero.com › aws › sagemaker › ml.g4dn.xlarge
ml.g4dn.xlarge SageMaker ML Instance Specs And Pricing
October 9, 2025 - CloudZero's intelligent platform helps you optimize cloud costs and improve infrastructure efficiency.
Aws-pricing
aws-pricing.com › g4dn.xlarge.html
g4dn.xlarge - Amazon EC2 Instance Type
2 weeks ago - Technical facts about the Amazon Elastic Compute Cloud (EC2) instance type g4dn.xlarge. Cost and pricing across all AWS locations for Amazon Elastic Compute Cloud (EC2) instance type g4dn.xlarge with free operating system.
EC2 Pricing Calculator
costcalc.cloudoptimo.com › aws-pricing-calculator › ec2 › g4dn.2xlarge
g4dn.2xlarge Pricing and Specs: AWS EC2
Explore the EC2 g4dn.2xlarge instance type and its costs across various regions, empowering you to make informed decisions for your cloud deployment strategy.