Alternatives
Products that do what A GPU group-buying layer to get enterprise rates (~50% off H100s) does
We built, saga[1] a layer that lets smaller teams access enterprise GPU discounts through collective buying power. How it works: 1. Aggregate GPU spend across hundreds of ML teams 2. Get enterprise rates through combined volume 3. Pass savings to users, monetize via provider partnerships Technical notes: - Works at billing layer only (no access to code/data) - Supports existing cloud setups or managed GPUs - Private beta running since January, opening more spots for March - Currently seeing ~50% savings on H100s/A100s [1] https://trysaga.ai
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Affordable H100, H200, GB300, and B200 GPU compute for training, inference, and everything in between.
3d ago · compute.cheap
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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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Hey we are Computable. We spent years building trading infrastructure at Jump Trading and Coinbase. From that point of view, compute looks like energy markets before 2000: everything trades through private bilateral leases, there’s no visible price, and nothing can be resold. The same H100 rents at a 2x spread depending on who’s asking, and once you sign a 24-month lease, it can never change hands. So we built a market for GPU nodes, sold by the calendar week. Here are three things you can do on it that you can’t do anywhere else: - Buy exactly the weeks you need. Three nodes for the last…
Jul 2026 · getcomputable.com
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The overall idea is to chart out the thousands of Mini PCs by benchmark and reveal the Pareto Front so you can get the most Compute per Dollar. Definitely a labor of love as I have a number of Mini PCs for my "homelab" (TrueNAS, piHole, Plex, basic stuff). It uses Gemini to extract specs from listings (since they're not often strongly categorized). Quick blog post here: https://luke.zip/posts/pareto-pcs/
Jun 2026 · minipcs.zip
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Hey HN! This idea started with me not being able to buy a GPU and constantly losing to bots/scalpers. I figured I'd use this as way to see how far I can get with 'vibe-coding and designing'*. The end result was pretty far! Here are more details of behind the scenes. In a future blog post, I'll detail behind the scenes process of building this. - The landing page is React/Typescript/Tailwind.css (which I've never used before) - The dashboard is based on Evidence.dev - which is SQL queries in Markdown + little bit of custom Javascript for chart formatting (again never used…
2025 · gpuisfine.singhkays.com
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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?
2024 · computeindex.michaelgiba.com
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2016 · github.com
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2024 · app.primeintellect.ai
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We'd like to introduce HN to Spell, which is a tool for easily running ML/DL jobs remotely. As Deep Learning has grown we see engineers and researchers struggle to incorporate running on GPUs into their workflow. So we built Spell to be the easiest way to get code running elsewhere - like the bash '&' operator but for remote machines. Sign up for an account at https://web.spell.run/waitlist, which includes $300 in credits for GPU time. There's a waitlist, but we'll be approving accounts as they come in. Here are some of the features we really wanted and built into Spell:…
2018
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GPU rental prices are super volatile but there's no derivatives market to hedge. I built a perpetual futures platform to see what this could look like. The idea is airlines hedge jet fuel, starbucks hedges coffee beans - as GPU compute becomes critical infrastructure the same hedging tools should exist. Not sure if anyone actually needs this but it was interesting to build. How it works: - Pulls live H200 spot prices from Vast.ai every 15s into a tradeable index - Full perp mechanics: funding rates, mark price calc, real-time P&L - Event-driven Rust backend with supervisor pattern and…
Feb 2026 · github.com
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I've made a GPU comparison site: https://gpu-prices.com/US/ Yes, there was one yesterday - I got beaten to it. This one is different in that I've put a lot of work into categorisation, so you can filter down quite precisely. For example, VRAM-per-dollar, limiting to Nvidia, and a minimum performance score allow you to find good ML GPUs. It currently supports Australia, Canada, Ireland, the UK, and the US. The tech stack is Python for data pull and static site generation then Cloudflare Pages for actually serving the site. It updates three times a day, but I could increase…
2024 · gpu-prices.com
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Hi HN! I've been hacking on this side project for the last month or two with the goal of making it dead simple to use cloud GPUs. I ran into this problem personally during the phd, and built my own tooling around it. I always thought it'd be fun to try to turn that tooling into a more general product... and bitbop.io is the result! All you have to do is run `ssh bitbop.io`, and you get your own personal dev GPU workstation in the cloud. Looking forward to hearing your thoughts!
2024 · twitter.com
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Jul 2026 · github.com
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Hi HN community, Shen and I created a service for anyone to easily train deep learning model on GPU power harnessed from the crowd. We have completed the first version DeepCluster.io (http://deepcluster.io) and welcome ML researchers to try it out for free! We are enthusiastic of deep learning, but often found training models with GPU instances on AWS very expensive. Meanwhile, some of our friends have idle GPUs that are used to mine cryptos. So we decided to borrow their GPUs for training deep learning model ourselves, and believe this could be a service that benefits other ML…
2019
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GPU cloud powered by idle gaming PCs — from $0.30/hr
Jun 2026 · technode.network
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