GPUHour
Live cloud GPU price comparison
What it does
Compare live cloud GPU rental prices across marketplaces, GPU clouds and hyperscalers — H100, H200, B200, RTX 4090 and more, spot and on-demand, refreshed from provider APIs.
Compare live GPU rental prices across clouds and marketplaces — pulled from provider APIs, not stale pricing pages. Cheapest live configuration per GPU per provider. Prices are whole-instance USD per hour divided by GPU count; click through for full configs. Data is polled from provider APIs every few hours. No hand-maintained spreadsheets: offers are pulled from each cloud's own pricing API on a rolling schedule, with the fetch time stored per offer. Vast.ai and Clore rigs next to RunPod, Verda, Vultr and the hyperscalers — spot and on-demand, consumer and datacenter silicon. Everything in this table is available at /api/v1/offers/ as JSON — filter by GPU, provider or pricing type. Tell us…from gpuhour.com
Does the same job
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Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
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Out of curiosity, I put together a simple website which tracks the prices for a few variations of A100/H100 GPUs by hour broken out between spot/ondemand, form factor and provider. Specifically I was tailoring the tool towards the smaller, emerging providers like runpod, gpulist.ai, lambda labs etc. Anyone have any ideas to expand/refine it?
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