Frustrated by GPU costs, so I built my own cloud

Hacker News

Hey HN, It was back in April 2023 when I was trying to build a voice agent with the Orpheus/Sesame CSM models it was my first time building something in AI and I absolutely hated the friction the platforms had to offer, mental prices, vast.ai instances not even connecting half of the time, and nothing in the platforms that said "you're welcome here" Out of frustration, I spoke to some providers, sorted out a fine list, and built Runcrate. We made the onboarding, UX, and overall experience as frictionless as possible. The billing is just like you'd pay OpenAI or Anthropic, no contracts, no reservations, no quotas, no more contacting support "Hey I need more GPUs pls" and then get rejected. Whatever is in the stock, its available for everyone. Oh and yeah, there's also a cool button that comes with all instances that spins up a vscode on the browser for you with a custom jupyter notebook extension installed. Frictionless, that's all I wanted in this space. I hope it'll genuinely help people looking to get started with AI & startups looking to cut their bills down. Would love your feedback pls Jish

Visit product View on Hacker NewsOct 27, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, models · Missing: mac, agents, macos

91%91% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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