g6f.large
⚡ 0.125x GPU • 3.0 GBPart of the G6F Accelerated Computing family — Hardware accelerators (GPUs, FPGAs) for specialized compute.
Name:
gGPU Graphics & ML Inferenceg = GPU Graphics & ML InferencePowered by GPUs (NVIDIA/AMD) for graphics-intensive applications, video encoding, remote workstations, and machine learning inference.66th Generation6 = 6th GenerationAWS 6th generation hardware platform with updated CPU/system architecture.fFast / FPGA Accelerationf = Fast / FPGA AccelerationEquipped with hardware accelerators for specialized compute, rendering, or FPGA execution.largeLargelarge = Large2 vCPUs • 8.0 GiB RAM • 100 GB NVMe SSD • Up to 10 Gigabit Network • 0.125x NVIDIA L4 (3.0 GB VRAM)Price (Linux)
$0.2020/ hr
~$147.46/mo
Compute
2vCPUs
1 cores • x86_64
Memory
8.0GiB
4.0 GiB / vCPU
Value
$0.1010/ vCPU-hr
$0.0253/GiB-hr
Network
10Gbps
Baseline: 1.5 Gbps
Storage & EBS
625MB/s
Max: 20,000 IOPS
Technical Specifications & Limits
Hardware specs, container thresholds, and system limitsCompute & Processor
ProcessorAMD EPYC 7R13 Processor
Architecturex86_64 (x86_64)
vCPUs / Threads2 vCPUs
Physical Cores1
Clock Speed2.6 GHz
Intel AVX / AVX2No
Intel Turbo BoostNo
Bare MetalNo (Virtualized)
Performance & Benchmarks
CoreMark Score40,677
CoreMark / vCPU20,338.6 / core
FFmpeg Transcoding17 FPS
CoreMark per Dollar201,371 score / $
Cost per vCPU-hr$0.1010
Cost per GiB-hr$0.0253
Containers & Kubernetes
EKS Max Pods20 pods
Max ECS Tasks10 tasks
Max ENIs2
IPv4/v6 per ENI10
Total Addressable IPs20 total IPs
CNI Prefix DelegationSupported (High Density)
Networking & Bandwidth
Network PerformanceUp to 10 Gigabit
Baseline Bandwidth1.5 Gbps
Burst / Peak Bandwidth10 Gbps
Enhanced NetworkingYes
EFA SupportNo
IPv6 SupportNative Dual-Stack Supported
Storage & EBS Optimization
Storage ConfigurationNVMe SSD (100 GB)
Local NVMe Disk100 GB
EBS Baseline Throughput117 MB/s
EBS Max Throughput625 MB/s
EBS Baseline IOPS3,750
EBS Max / Burst IOPS20,000
Dedicated EBS ThroughputUp to 5000 Mbps
GPU & Hardware Acceleration
GPU ModelNVIDIA L4
Accelerator Count0.125x GPU(s)
Total GPU Memory3.0 GB
Memory ArchitectureGDDR / HBM
CUDA Compute Capabilityv10.0
Acceleration RuntimesCUDA, TensorRT, cuDNN, PyTorch, PyJAX
Platform & Architecture Details
Hypervisor / SystemAWS Nitro System (PCIe Offload)
Nitro EnclavesNot Supported
Normalization FactorNA
Generation StatusCurrent Generation (Recommended)
Date Introduced2025-07-29
Regional Pricing Matrix
Live on-demand rates across all global AWS cloud regionsLowest Price Region
$0.2020/ hr
US East (N. Virginia) (us-east-1)Highest Price Region
$0.3434/ hr
South America (Sao Paulo) (sa-east-1)Global Fleet Average
$0.2439/ hr
Across all active regionsRegional Coverage
13regions
Available worldwide| Region Name | Region Code | On-Demand Price |
|---|---|---|
Asia Pacific (Mumbai) | ap-south-1 | $0.2426 |
Asia Pacific (Seoul) | ap-northeast-2 | $0.2484 |
Asia Pacific (Sydney) | ap-southeast-2 | $0.2626 |
Asia Pacific (Tokyo) | ap-northeast-1 | $0.2930 |
Canada (Central) | ca-central-1 | $0.2243 |
EU (Frankfurt) | eu-central-1 | $0.2526 |
EU (London) | eu-west-2 | $0.2564 |
EU (Stockholm) | eu-north-1 | $0.2142 |
Europe (Spain) | eu-south-2 | $0.2273 |
South America (Sao Paulo)Highest | sa-east-1 | $0.3434 |
US East (N. Virginia)Lowest | us-east-1 | $0.2020 |
US East (Ohio)Lowest | us-east-2 | $0.2020 |
US West (Oregon)Lowest | us-west-2 | $0.2020 |
| Region Name | Region Code | On-Demand Price |
|---|---|---|
Asia Pacific (Mumbai) | ap-south-1 | $0.3346 |
Asia Pacific (Seoul) | ap-northeast-2 | $0.3404 |
Asia Pacific (Sydney) | ap-southeast-2 | $0.3546 |
Asia Pacific (Tokyo) | ap-northeast-1 | $0.3850 |
Canada (Central) | ca-central-1 | $0.3163 |
EU (Frankfurt) | eu-central-1 | $0.3446 |
EU (London) | eu-west-2 | $0.3484 |
EU (Stockholm) | eu-north-1 | $0.3062 |
Europe (Spain) | eu-south-2 | $0.3192 |
South America (Sao Paulo)Highest | sa-east-1 | $0.4354 |
US East (N. Virginia)Lowest | us-east-1 | $0.2940 |
US East (Ohio)Lowest | us-east-2 | $0.2940 |
US West (Oregon)Lowest | us-west-2 | $0.2940 |
No regions matched your search filter.