Cloud Provider Benchmarks

Cloud provider benchmarks, comparisons and infrastructure research

The tracked providers are AWS, PortvMind Cloud, Google Cloud, Microsoft Azure, DigitalOcean, Vultr and Hetzner. Every figure links to its source and every method is written out in full. Values derived from specifications are labelled as derived, not as measurements.

Benchmarks Compare providers Research

Providers tracked: 7
Benchmark categories: 15
Research articles: 16
Verified runs: 0; Measured results are added as runs complete

Benchmarks

What we measure

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Compute

How we benchmark cloud virtual machines: CPU throughput, memory bandwidth, boot time and price-performance across AWS, PortvMind Cloud, Google Cloud, Azure and more.
GPU & AI

Compare NVIDIA H100, H200 and L40S cloud GPUs for LLM inference: specifications, memory capacity models, provider availability, list prices and verified runs.
Block storage

How we benchmark cloud block storage volumes with fio: random 4K IOPS, sequential throughput, latency percentiles, snapshot support and pricing by provider.
Object storage

Benchmarking S3-compatible object storage across PortvMind, AWS S3, DigitalOcean Spaces, Vultr and Hetzner: PUT/GET throughput, latency and API coverage.
Network

How we measure cloud networking: VM-to-VM bandwidth with iperf3, latency to Istanbul and Frankfurt, and load balancer, floating IP and NAT capabilities.
Kubernetes

Comparing managed Kubernetes services, including PortvMind VKE, EKS, AKS, GKE, DOKS and Vultr VKE, on cluster creation time, autoscaling and integrations.
Cloud security

A qualitative comparison of documented cloud security capabilities: security groups, private networks, audit logging, identity attribution and certifications.
Cloud auditing

How cloud audit logging services record who did what: scope, identity, request metadata, search, retention and export for vTrail, CloudTrail, Azure and GCP.
Price-performance

Normalised cloud pricing: implied per-vCPU and per-GiB hourly prices, per-GPU-hour list prices, billing granularity and the sources behind every figure.

GPU & AI

GPU analysis for LLM inference

Model fit, KV-cache capacity and decode ceilings for H100, H200 and L40S, across Qwen, Llama, DeepSeek and MiniMax models.

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Hopper

NVIDIA H100

Hopper-generation data-centre GPU with 80 GB of HBM3 (SXM) and FP8 Transformer Engine support; the reference accelerator for LLM training and high-throughput inference.
Hopper

NVIDIA H200

Hopper-generation GPU with 141 GB of HBM3e at 4.8 TB/s — the same Tensor Core compute as H100 SXM with 1.76× the memory and 1.43× the bandwidth.
Ada Lovelace

NVIDIA L40S

Ada Lovelace universal data-centre GPU with 48 GB of GDDR6 at 864 GB/s and FP8 support — a lower-cost option for inference of small and mid-size models, graphics and video.

Research

Latest research

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Provider discovery

AWS alternatives with infrastructure in Türkiye

AWS, PortvMind Cloud, Google Cloud, Azure and the other tracked providers when a workload needs an AWS alternative in Türkiye.

6 November 2026
Cloud security & auditing

AWS CloudTrail alternatives: audit logging on other clouds and OpenStack

CloudTrail's equivalents on Google Cloud, Azure, OpenStack-based clouds and smaller providers, compared on scope, identity, retention, export and integrity.

6 November 2026
GPU & AI infrastructure

Best GPU for LLM inference: matching H100, H200 and L40S to model size

Which GPU to use for LLM inference by model size, precision, context length and concurrency — a sizing guide for Qwen, Llama, DeepSeek and MiniMax.

6 November 2026
Cloud security & auditing

Cloud activity monitoring: how audit logs, alerts and metrics fit together

The difference between cloud audit logging, activity monitoring and performance monitoring, and how to build alerts on audit events across providers.

6 November 2026
Cloud security & auditing

Cloud audit logging compared: CloudTrail, vTrail, Google Cloud Audit Logs and Azure Activity Log

How cloud providers record who did what and when: scope, identity, request metadata, retention, export and integrity across four audit-logging services.

6 November 2026
Cloud security & auditing

Cloud audit trail best practices: coverage, retention, integrity and review

A practical checklist for cloud audit trails: what to log, how long to keep it, how to protect it from tampering and how to review it, mapped to provider features.

6 November 2026