flopper.io

What It Is

Flopper.io is a GPU performance and specifications database for AI infrastructure selection. It collects and normalizes data center GPU / AI accelerator information from vendors such as NVIDIA, AMD, Intel, and Google, covering 96+ GPUs, 607 global GPU data centers, and multiple system form factors including DGX, HGX, NVL, OAM, and multi-GPU clusters. Its core value is bringing metrics scattered across datasheets, white papers, and benchmarks into a searchable, filterable interface for side-by-side comparison.

Core Capabilities

In terms of features, Flopper.io offers a GPU Database, Compare Specs, FLOPS Calculator, AI Systems, and a Datacenter Map. Users can compare peak TFLOPS, VRAM, TDP, memory bandwidth, and architecture across precisions such as FP64, FP32, FP16, BF16, FP8, TF32, INT8, and FP4. The FLOPS Calculator can estimate aggregate compute, power consumption, and memory for custom GPU configurations, making it useful for rough capacity planning before training-cluster builds or inference deployments. The site also provides guides on Apple Silicon, NVIDIA architectures, Hopper vs Blackwell, and data center GPU selection, with generally clear explanatory documentation.

Pricing and Openness

The main site indicates that the core tools are free to use. On the commercial side, there are listing and advertising options for GPU providers: a Provider listing costs $599 as a one-time fee, while advertising costs $999/month, both excluding tax; free listings can be requested via a queue. The GPU Pricing Tool is still marked as Coming Soon, so cloud GPU rental price comparison and price alerts are not yet fully available. No open-source information, API/SDK, CLI, data export, or self-hosting documentation was found.

Pros and Cons

The strengths are normalized metrics, fine-grained precision categories, and data points that emphasize linked sources, which can significantly reduce the time engineers spend cross-checking multiple PDFs. It also puts performance, memory, power consumption, system configuration, and data center location into the same context, making it useful for procurement and architecture discussions. The limitations are that its FLOPS figures use vendors’ ideal peak numbers, including sparsity acceleration and theoretical performance, so real workloads still need empirical validation. It also lacks clear information on APIs, private deployment, SLAs, and payment methods, making it less explicit for teams that need automated integration.

Who It’s For and Access from China

Flopper.io is suitable for AI/ML engineers, HPC engineers, researchers, infrastructure procurement teams, and industry analysts for initial GPU screening, performance interpretation, and power/memory planning. Access from China is not mentioned in the main content and should be tested directly. If access or payment is limited, it can be cross-checked against alternative sources such as official NVIDIA/AMD/Intel specification pages, MLPerf, TechPowerUp GPU Database, and cloud provider instance pricing pages.