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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 › instance types › g4 instances

Amazon EC2 G4 Instances — Amazon Web Services (AWS)

5 days ago - They provide up to 8 NVIDIA T4 GPUs, 96 vCPUs, 100 Gbps networking, and 1.8 TB local NVMe-based SSD storage and are also available as bare metal instances. G4dn instances are equipped with NVIDIA T4 GPUs which deliver up to 40X better low-latency throughput than CPUs, so more requests can be ...

Vantage

instances.vantage.sh › aws › ec2 › g4dn.4xlarge

g4dn.4xlarge pricing and specs - Vantage

The g4dn.4xlarge instance is in the GPU instance family with 16 vCPUs, 64 GiB of memory and up to 25 Gibps of bandwidth starting at $1.204 per hour.

Vantage

instances.vantage.sh › aws › ec2 › g4dn.8xlarge

g4dn.8xlarge pricing and specs - Vantage

The g4dn.8xlarge instance is in the GPU instance family with 32 vCPUs, 128 GiB of memory and 50 Gibps of bandwidth starting at $2.176 per hour.

EC2 Pricing Calculator

costcalc.cloudoptimo.com › aws-pricing-calculator › ec2 › g4dn.xlarge

g4dn.xlarge Pricing and Specs: AWS EC2

The g4dn.xlarge instance is part of the g4dn series, featuring 4 vCPUs and Up to 25 Gigabit of RAM, with Gpu Instances.

NVIDIA Developer

developer.nvidia.com › blog › getting-the-most-out-of-nvidia-t4-on-aws-g4-instances

Getting the Most Out of NVIDIA T4 on AWS G4 Instances | NVIDIA Technical Blog

August 21, 2022 - Using BERT Large, which is about three times larger than BERT Base, you can get a million sentences inferenced for around 30 cents. The efficiency of the T4 GPU that powers the AWS g4dn.xlarge instance means you can cost effectively deploy smart, ...

VPSBenchmarks

vpsbenchmarks.com › home › gpu plans › amazon aws › g4dn.xlarge gpu plan

g4dn.xlarge GPU Plan | VPSBenchmarks

This plan belongs to the Amazon AWS G4 server line (GPUs).

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

Beta Notice · CloudZero Advisor's AI is currently in BETA and may provide inaccurate information · Learn More · Switch Theme · Toggle menu · Sign In · Gathering instance details, stand by · Privacy•Terms•Support

CloudPrice

cloudprice.net › amazon web services › ec2 › g4dn.2xlarge

g4dn.2xlarge specs and pricing | AWS | CloudPrice

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.

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reddit.com › r/aws › is g4dn.xlarge better than g6.xlarge?

r/aws on Reddit: Is g4dn.xlarge better than g6.xlarge?

May 28, 2025 -

I checked few websites and it showed T4 gpu outperforms L4 gpu.

g4dn.xlarge uses T4 g6.xlarge uses L4

Is CPU the bottleneck in these instances? Has anyone perf tested these two for inference?

Top answer

1 of 3

I'm really not sure what sites you are looking at, but if you look at the official spec sheets, L4 is much more performant than T4: 242 Tflops FP16 vs 65 Tflops FP16. https://www.nvidia.com/en-us/data-center/l4/ https://www.nvidia.com/en-us/data-center/tesla-t4/ It also makes sense that this is the case. T4 is several generations older than L4, and both cards have similar powerdraw.

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g6e (L40S) is significantly more performant than either of those

reddit.com › r/aws › g4dn.large instances

r/aws on Reddit: G4dn.large Instances

September 4, 2025 -

Hi all, I’ve been searching regions but can’t seem to locate any available g4dn.large instances. Have they been deprecated, or are they simply unavailable due to high demand? Thank you for the insight!

Top answer

1 of 3

Lol, funny timing, I was just in this same area today, and this was what I found: "g4dn.xlarge — that’s the smallest in the g4dn family (1× T4 GPU, 4 vCPU, 16 GiB RAM)."

2 of 3

Couple of questions! Are you getting insufficient capacity errors? If not, what error are you getting? Is this only in reference to g4dn.xlarge instances or the whole g4dn family? What regions are you experiencing this in?

CloudPrice

cloudprice.net › amazon web services › ec2 › g4dn.xlarge

g4dn.xlarge specs and pricing | AWS | CloudPrice

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.

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 December 2020, AWS released the Amazon EC2 G4ad instance subfamily — powered by AMD Radeon Pro V520 GPUs and second-generation AMD EPYC processors with up to 2.4 TB of local NVMe storage — that delivers up to 40% better price performance ...

Vantage

instances.vantage.sh › aws › ec2 › g4dn.2xlarge

g4dn.2xlarge pricing and specs - Vantage

The g4dn.2xlarge instance is in the GPU instance family with 8 vCPUs, 32 GiB of memory and up to 25 Gibps of bandwidth starting at $0.752 per hour.

EC2 Pricing Calculator

costcalc.cloudoptimo.com › aws-pricing-calculator › ec2 › g4dn.8xlarge

g4dn.8xlarge Pricing and Specs: AWS EC2

The g4dn.8xlarge instance is part of the g4dn series, featuring 32 vCPUs and 50 Gigabit of RAM, with Gpu Instances.

AWSstatic

d1.awsstatic.com › events › reinvent › 2021 › How_to_select_Amazon_EC2_GPU_instances_for_deep_learning_sponsored_by_NVIDIA_CMP328-S.pdf pdf

Best single-GPU instance for developing, testing, and prototyping: g4dn.xlarge (T4, 16 GB GPU); consider

Computer Weekly

computerweekly.com › news › 252471099 › AWS-G4-aims-to-lower-cost-of-GPU-powered-AI-inference

AWS G4 aims to lower cost of GPU-powered AI inference | Computer Weekly

“According to customers, machine learning inference can represent up to 90% of overall operational costs for running machine learning workloads.” · On-demand pricing of the g4dn.xlarge, four virtual core instance, with one GPU and 16GB ...

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

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

2 of 3

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?

reddit.com › r/stablediffusion › rtx 3060 vs aws g4dn.xlarge

r/StableDiffusion on Reddit: RTX 3060 vs AWS g4dn.xlarge

May 30, 2023 -

Hi guys,

I'm using SD on AWS g4dn.xlarge and I'm pretty happy with the results. Sometimes I'm getting 'Out of memory', but restarting A1111 fixes the problem.I'm going to buy RTX 3060, with a price of it comparing to what I pay to AWS, I can recoup it in 3+ months.

I can't find any comparations to check.Maybe someone can make a test with RTX 3060 and run this prompt:

((photo:1.2)), A cute cat mage, glowing fire sword, staff, dramatic lighting, dynamic pose, dynamic camera, masterpiece, best quality, dark shadows, ((dark fantasy)), detailed, realistic, 8k uhd, high quality((photo:1.2)), A cute cat mage, glowing fire sword, staff, dramatic lighting, dynamic pose, dynamic camera, masterpiece, best quality, dark shadows, ((dark fantasy)), detailed, realistic, 8k uhd, high qualityNegative prompt: canvas frame, (high contrast:1.2), (over saturated:1.2), (glossy:1.1), cartoon, 3d, ((disfigured)), ((bad art)), ((b&w)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), cloned face, (((disfigured))), extra limbs, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands, (fused fingers), (too many fingers), (((long neck))), Photoshop, video game, ugly, tiling, poorly drawn hands, 3d render, ((watermarks)), smooth, plastic, blurry, low-resolution, deep-fried, oversaturatedSteps: 30, Sampler: Euler a, CFG scale: 7, Seed: 408625209, Size: 512x512, Model hash: cc6cb27103, Model: v1-5-pruned-emaonly, Version: v1.5.1

Model: v1-5-pruned-emaonlyIt took 5 sec. and 5.35it/s - 5.48it/s to generate an 512*512 image on AWS.

What it/s you've got on RTX 3060?

Thank you so much.

Top answer

1 of 3

Just a small update. At last I've got my RTX 3060 12GB. I got just a little performance improvements over AWS. I'm getting 6+ it/s and for the prompt above I got 4 seconds for each image. There is my command line options to start: --xformers --medvram --opt-sdp-no-mem-attention --no-half-vae

2 of 3

Steps: 30, Sampler: Euler a, CFG scale: 7, Seed: 408625209, Size: 512x512, Model hash: cc6cb27103, Model: ver 1-5, Version: v1.5.1-495-g541ef924 Time taken: 6.5 sec. A batch of 8 takes 31.4 seconds, so a bit less than 4 sec/image. (I really think you need to cut down on the length of the prompts. Most of the stuff, especially in the negative prompt, is fluff that probably doesn't help one bit.)