1.32 Petaflops hardware for local prototyping

Hacker News

I’ve been working on Vanta, a scalable AI hardware solution powered by 2–8 NVIDIA RTX 4090s, delivering up to 1.32 petaflops FP32 in a compact form factor. It’s built for startups, developers and researchers to prototype, fine-tune and run models up to 70B parameters locally. So you can own your computer instead of renting. - A 2-GPU setup costs $9k and breaks even in 9 months vs. cloud rental at $0.69/hr (ex: RunPod). - The 8-GPU at $40k saves $12k in year one compared to $48k in cloud costs. This can handle different AI framework: TensorFlow, PyTorch, ONNX, CUDA-optimized libraries, VLLM, SGLANG, llama.cpp... I can get it built in a day and shipped out quick. Let me know what you think!

Visit product View on Hacker NewsMar 18, 2025

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

84%84% 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: para · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: llama, io · Missing: https docs, excited, just released

72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month, para · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% 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.

Incorrect prediction on native model

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