Alternatives
Products that do what GPUSignals does
Track&predict GPU power availability across cloud platforms.
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Hi HN, YC w24 company here. We just pivoted from drone delivery to build gpudeploy.com, a website that routes on-demand traffic for GPU instances to idle compute resources. The experience is similar to lambda labs, which we’ve really enjoyed for training our robotics models, but their GPUs are never available for on-demand. We are also trying to make it more no-nonsense (no hidden fees, no H100 behind “contact sales”, etc.). The tech to make this work is actually kind of nifty, we may do an in-depth HN post on that soon. Right now, we have H100s, a few RTX 4090s and a GTX 1080 Ti online.…
2024 · gpudeploy.com
- 2SS
Hi HN, we are Ed, Zach, and Ronald, creators of Shadeform (https://www.shadeform.ai/), a GPU marketplace to see live availability and prices across the GPU market, as well as to deploy and reserve on-demand instances. We have aggregated 8+ GPU providers into a single platform and API, so you can easily provision instances like A100s and H100s where they are available. From our experience working at AWS and Azure, we believe that cloud could evolve from all-encompassing hyperscalers (AWS, Azure, GCP) to specialized clouds for high-performance use cases. After the launch of…
2023 · shadeform.ai
- 3TC
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…
2022 · tensordock.com
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2021 · gpu.land
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General Compute▲315AI models that run on an inference cloud optimized for speed
May 2026 · generalcompute.com
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Greetings HN! This is Doruk from Oblivus, and I'm excited to announce the launch of our platform, Oblivus Cloud. After more than a year of beta testing, we're excited to offer you a platform where you can deploy affordable and scalable GPU virtual machines in as little as 30 seconds! https://oblivus.com/cloud - What sets Oblivus Cloud apart? At the start of our journey, we had two primary goals in mind: to democratize High-Performance Computing and make it as straightforward as possible. We understand that maintaining GPU servers through major cloud service providers can be…
2023 · oblivus.com
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2023 · vram.asmirnov.xyz
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The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com
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2022 · paylesstoaws.com
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2016 · github.com
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- 20TG
Hey folks! I’m Jonathan from TensorDock, and we’re building a cloud GPU marketplace. We want to make GPUs truly affordable and accessible. I once started a web hosting service on self-hosted servers in middle school. But building servers isn’t the same as selling cloud. There’s a lot of open source software to manage your homelab for side projects, but there isn’t anything to commercialize that. Large cloud providers charge obscene prices — so much so that they can often pay back their hardware in under 6 months with 24x7 utilization. We are building the software that allows anyone to become…
2024 · dashboard.tensordock.com
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2021 · inferrd.com
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