Stateful AI API with OS Models

Hacker News

We just launched ARK Cloud API: OpenAI‑compatible, stateful AI inference service that keeps context across calls to slash token spend (0.01 USD / 1M input tokens), spins up in 10 s with Google SSO, runs fully on GDPR‑strong EU‑only infra, and gives 50 000 free credits at signup. Supports Stable Diffusion (cheapest rates), Llama 8 & 70B, embeddings, STT and more. PAYG, no logs, no data stored ark-labs.ai

Visit product View on Hacker NewsJul 31, 2025

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Launch Intel predictions

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

87%87% 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: supports, compatible · Missing: reddit linkedin, podcasting, created

86%86% 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, 000, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal

65%65% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: calls · 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

27%27% 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

25%25% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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