- 1Azure NC24ads A100 v4$4 / GPU-hr
- 2Azure ND96amsr A100 v4$4 / GPU-hr
- 3Azure NC40ads H100 v5$7 / GPU-hr
Free public boards
Infrastructure
The compute, data centers, power, chips and clouds the AI build out runs on, priced and counted from public filings and official releases.
Where it stands today
Open the first board →Today's leaders across the infrastructure boards.
3 of the boards on this page, as it published in the latest run. Every figure links back to the filing, release or price list it came from.
Estimated AI compute ownership by companyEstimated owned compute (median)
- Google5,453,215 H100e
- Microsoft3,574,563 H100e
- Amazon2,508,034 H100e
Operational AI data centersFacility power
- Colossus 2946 MW
- Anthropic-Amazon New Carlisle910 MW
- Microsoft Fairwater Atlanta636 MW
Planned AI data center capacityFacility power
- Microsoft Fairwater Wisconsin2,715 MW
- OpenAI Stargate New Mexico2,450 MW
- Anthropic-Amazon New Carlisle2,310 MW
Every AI answer costs power, land and silicon.
These boards price the parts that cannot scale on demand.
Counted from official releases, utility filings and published price lists.
Pick your board
Every live infrastructure board
All 42 boards are free to read and link to the evidence behind every row. Refresh rates differ by board and are shown on each one.
Compute
What an hour of GPU time costs, and who owns the most of it.
- 1AWS EC2 g6.xlarge$0.805 / GPU-hr
- 2AWS EC2 g6.12xlarge$1 / GPU-hr
- 3AWS EC2 g6e.xlarge$2 / GPU-hr
- 1NVIDIA GTX1050 2 GB PCIe$0.050 / GPU-hr
- 2NVIDIA GTX1070TI 8 GB PCIe$0.080 / GPU-hr
- 3NVIDIA RTX 3090 24 GB PCIe$0.120 / GPU-hr
- 1Google5,453,215 H100e
- 2Microsoft3,574,563 H100e
- 3Amazon2,508,034 H100e
Datacenters
Where capacity is being built, and how much power it will need.
- 1Colossus 2946 MW
- 2Anthropic-Amazon New Carlisle910 MW
- 3Microsoft Fairwater Atlanta636 MW
- 1Microsoft Fairwater Wisconsin2,715 MW
- 2OpenAI Stargate New Mexico2,450 MW
- 3Anthropic-Amazon New Carlisle2,310 MW
- 1Amazon U.S. Federal AI & HPC Infrastructure$50
- 2Amazon Pennsylvania AI & Cloud Infrastructure$20
- 3Amazon Northern Indiana Data Centers$15
- 1Pennsylvania2 projects
- 2Indiana1 projects
- 3Louisiana1 projects
- 1Texas7,165.3 MW
- 2Wisconsin4,015 MW
- 3Indiana3,345 MW
Power
What electricity costs by state, and how clean each grid is.
- 1New Mexico4.62¢/kWh
- 2Texas6.58¢/kWh
- 3Montana6.68¢/kWh
- 1Vermont52 pounds per megawatt hour
- 2Washington267 pounds per megawatt hour
- 3New Hampshire276 pounds per megawatt hour
Chips & memory
Memory, bandwidth and supply across the accelerators everyone is waiting on.
- 1AMD Instinct MI325X256 GB
- 2AMD Instinct MI300X192 GB
- 3NVIDIA B200 SXM180 GB
Vector databases
Who AI recommends when a buyer asks about Vector DBs, and which pages those answers cite.
- 1Pinecone46%
- 2Weaviate46%
- 3Qdrant38%
- 1Pinecone33%
- 2Weaviate31%
- 3Qdrant31%
- 1Qdrant27%
- 2Redis27%
- 3Pinecone12%
- 1Pinecone3 engines
- 2Weaviate3 engines
- 3Qdrant3 engines
- 1What is the best serverless or usage-based vector database for a startup with an unpredictable retrieval workload?100%
- 2Recommend an open-source vector database that an engineering team can self-host in its own cloud account.100%
- 3Recommend a low-latency vector search system for a workload that may grow to billions of embeddings.67%
- 1Which enterprise vector retrieval services offer private networking, access controls, compliance, and regional deployment?100%
- 2How should a team compare vector database pricing across storage, ingestion, read throughput, replicas, and idle capacity?100%
- 3Recommend a low-latency vector search system for a workload that may grow to billions of embeddings.96%
- 1reddit.com36%
- 2medium.com25%
- 3qdrant.tech19%
Engine by engine
The same brands, scored inside one assistant at a time. The order changes, and so does the gap.
Cloud GPU platforms
Who AI recommends when a buyer asks about GPU clouds, and which pages those answers cite.
- 1Runpod46%
- 2Google Cloud42%
- 3Microsoft Azure38%
- 1Runpod39%
- 2Google Cloud36%
- 3Microsoft Azure28%
- 1Runpod50%
- 2Lambda Cloud15%
- 3Google Cloud12%
- 1Runpod2 engines
- 2Google Cloud2 engines
- 3Microsoft Azure2 engines
- 1Compare cloud GPU platforms on availability, accelerator breadth, interconnect, storage, reliability, support, and developer experience.67%
- 2Which GPU clouds offer strong managed Kubernetes or Slurm support for distributed AI training and inference?67%
- 3Recommend cloud GPU providers with transparent on-demand access to H100 or H200 instances and no long-term commitment.67%
- 1Compare cloud GPU platforms on availability, accelerator breadth, interconnect, storage, reliability, support, and developer experience.92%
- 2Which GPU clouds offer strong managed Kubernetes or Slurm support for distributed AI training and inference?92%
- 3Recommend cloud GPU providers with transparent on-demand access to H100 or H200 instances and no long-term commitment.87%
- 1runpod.io36%
- 2northflank.com22%
- 3reddit.com22%
Engine by engine
The same brands, scored inside one assistant at a time. The order changes, and so does the gap.
Cloud platforms
Who AI recommends when a buyer asks about Cloud, and which pages those answers cite.
- 1Amazon Web Services67%
- 2Google Cloud67%
- 3Microsoft Azure67%
- 1Amazon Web Services56%
- 2Google Cloud52%
- 3Microsoft Azure52%
- 1Google Cloud31%
- 2IBM Cloud31%
- 3DigitalOcean19%
- 1Amazon Web Services3 engines
- 2Google Cloud3 engines
- 3Microsoft Azure3 engines
- 1What cloud platform should a startup evaluate for predictable costs, simple deployment, developer support, and room to scale?100%
- 2Recommend cloud providers for organizations that need sovereign deployment options, broad regional coverage, and data-residency controls.67%
- 3How should a buyer compare cloud pricing, discounts, support plans, network egress, and total operating cost?67%
- 1Recommend cloud providers for organizations that need sovereign deployment options, broad regional coverage, and data-residency controls.94%
- 2How should a buyer compare cloud pricing, discounts, support plans, network egress, and total operating cost?89%
- 3Which cloud platform is best for a governed lakehouse, streaming analytics, business intelligence, and machine learning stack?80%
- 1reddit.com13%
- 2ibm.com10%
- 3medium.com8%
Engine by engine
The same brands, scored inside one assistant at a time. The order changes, and so does the gap.