The $140B Compute Arbitrage AI compute costs are skyrocketing. Fine tuning a model on AWS can cost $11.27/hour for an H100 GPU, while Aethir offers the same job for $1.25/hour, saving a single team $8K/month. Scaled across AI’s $80–150B market by 2027, this is the biggest infrastructure arbitrage since the move to cloud. Enterprises hesitate due to perceived risks: decentralized networks, crypto tokens, and regulatory concerns. DePIN is overhyped yet underutilized, lacking institutional infrastructure. Market Reality: DePIN generated $64M in fees by Q3 2025 (5x YoY growth). Aethir alone serves 150+ enterprise clients at a $166M ARR. Savings are best on batch workloads (overnight training, rendering, synthetic data), while critical APIs and regulated data still favor cloud. The Institutional Barrier: $5–10B of opportunity is locked by compliance gaps: unclear SLAs, data residency, and legal ambiguity. ArgentumAI targets this, offering compliance-first infrastructure. Live Use Cases: Aethir: Regional gaming compute, 65% cheaper and faster than AWS. Akash: AI lab model evaluation, 59% cost reduction. Render: VFX studios, 60–70% cheaper rendering. io[.]net: Startup access to 40x H100 GPUs in 48 hours, 70% cheaper. Nosana: DeFi CI/CD, 80% cost savings. Argentum AI : Institutional DePIN Focuses on idle enterprise GPUs (V100s, P100s, RTX A-series) as revenue assets. Compliance-first: DAO LLC, KYC/AML for providers, regional pinning, SLA escrow. Targets CIOs, labs, and regulated enterprises, not just crypto-native devs. Why It Matters: Compliance-first networks can unlock institutional spend and idle hardware. DePIN adoption is already happening at scale, but execution risk remains: liquidity, competitive response, and enterprise onboarding. DePIN is no longer theoretical, enterprise-grade providers like @Argentum_AI prove the model works for regulated workloads, offering massive cost arbitrage while bridging compliance gaps.